فهرست مطالب محمدعلی خاتمی فیروزآبادی

Evaluation of performance and productivity and the process of its changes over time is considered essential in the process of improvement in organizations, production, industrial and service units. Regarding the calculation of productivity and changes in productivity over time, different models, methods, approaches, and indices have been presented; one of the most important, common and widely used is the Malmquist productivity index. On the other hand, during production processes, undesirable products and outputs are obtained simultaneously with desirable products. Therefore, an index called Malmquist Luenberger was presented with the development of Malmquist's productivity index, which took into account the undesirable outputs while seeking to reduce them and, at the same time, aimed at expanding the desirable outputs. Therefore, the current research has been compiled with the aim of a structured and systematic review and analysis of articles and research that have made a scientific effort on the subject of calculating productivity changes in units with undesirable output using the Malmquist productivity index and especially the Malmquist Luenberger productivity index. This research is based on PRISMA methodology with the aim of structured analysis of studies that have made a scientific effort in the field of calculating productivity changes in units with undesirable output using the Malmquist/Malmquist Luenberger productivity index. This research is a review type that was conducted through searching in domestic and foreign databases such as academic information, Scopus, Science Direct, Elsevier, and Google Scholar in the period from 1980 to 2022 with the approach of selecting the most important, valid, and prominent domestic and foreign scientific and applied articles and researches. In terms of the quantity and quality of the articles, the present article seems to be unprecedented and unique because, due to the breadth and diversity of published articles and research, the void of the current structured research among the published efforts is quite noticeable, and by using this article, on the one hand, researchers can study the latest actions and research efforts in the mentioned field in a completely categorized and structured manner, and on the other hand, the existing scientific gaps and future proposals regarding the evaluation of benefits. See the productivity using the Malmquist/Malmquist Luenberger productivity index, which is the result of the scientific investigations of the authors of this article. Therefore, this research, in the form of a structured review and analysis article, is considered a kind of road map for researchers interested in the field of productivity.Originality/Value: Considering that this article is a structured review of existing research, the output of the current research is a roadmap for researchers and researchers in the field of calculating productivity changes using the Malmquist/Malmquist Luenberger index in order to understand the current problems, challenges and problems of current research as well as future scientific proposals.

Today, resilience is a topic that has attracted increasing interest in the business space. Uncertainty about the future, changes, developments and environmental risks have endangered the survival of today's organizations. Managers of most organizations believe that the resilience of businesses plays an important role in enabling them to invest, sell, market, trade, etc. in the future. On the other hand, the lack of a systematic and efficient study and the existence of a model about the resilience of small and medium businesses in internal and external research has become the main problem of the managers of these companies. Therefore, in this research, the factors affecting the resilience of companies have been investigated in order to adopt effective strategies in order to prevent and prevent disruptions and reduce the performance of companies using system dynamics methods. Considering the importance of the development of small and medium-sized companies in the current state of the country from the economic, security, political, health and other situations, it is necessary to prevent financial and functional helplessness and bankruptcy, therefore, the findings of this research include identifying the factors that contribute to the resistance of small and medium-sized companies with Considering environmental drivers and impulses are effective and presenting a conceptual and operational model of organizational resilience. The research method of the current research is practical in terms of its purpose and it is exploratory in terms of data collection, and the type of research data is qualitative and quantitative.

Nowadays insurance companies, same as other companies, are facing massive competition. This issue indicates the value of customer loyalty also a predictive model. Customers play a crucial role in the sustainability of organizations by constant repurchasing. Companies with loyal customers have more market share, and more money may return on investment. This article's main aim is to identify the factors affecting customer loyalty in insurance companies.

This research was quantitative, analytical-descriptive. In gathering information, Data was collected through the survey, and the findings are practical. In this way, two methods, Confirmatory Factor Analysis (CFA) and Artificial Neural Networks (ANN) were used. For localizing the factors extracted from other similar prior literature, first, the elements were examined by CFA with SMART PLS application due to some conflicts in the literature to evaluate whether each factor affects customer loyalty or not. Then, the elements were introduced to the ANN for training by this program.

In this article, by using the MORGAN table, the sample size detected 384 people in 0.05 error. Questionnaires were distributed randomly between four Iranian insurance companies, ASIA insurance company, ALBORZ insurance company, and PARSIAN insurance company. Based on Confirmatory Factor Analysis, elements of commitment, perceived quality, trust, perceived value, empathy, brand image, the attraction of other alternatives, and customer satisfaction impact the customer loyalty of insurers in these companies. The cost of change, nevertheless, did not have a significant effect on customer loyalty. Then, the factors used as inputs for the multi-layer perceptron training also customer loyalty are indicated as output. The model was designed with eight inputs, 110 nodes in the hidden layer, and one output the error was E= 0.00992 and the regression = 0.98684.

Originality/Value: 

the finding of this research is, expanding a model for predicting customer loyalty in Iranian insurance companies.

Today, ground transportation systems are facing a major challenge which has come to be known as traffic congestion. Since traffic and congestion are complex and dynamic phenomena, it is difficult and sometimes impossible to apply conventional mathematical models on them. Thus agent-based technologies with high compatibility with the afore-mentioned characteristics can be used to model the phenomenon of congestion and detect effective congestion mitigation/aggravation parameters. Considering the role of bus rapid transit in the transportation of passengers, mitigation of congestion and reduction of passenger waiting time and travel time are among the objectives of the present study. Therefore, agent-based simulation of the movement of bus rapid transit (BRT) fleets is used to achieve the afore-mentioned goal. In the present study, NetLogo is used to code the model and run the simulation. Three different scenarios were taken into account in this study. Change of effective factors in each of the three scenarios led to significant improvements in the BRT performance analysis results. Finally, after general analysis and comparison of different scenarios, results and suggestions were presented to improve the performance of BRT fleets. In the attempt to achieve the goals (i.e. reduction of passenger waiting time at stations and reduction of travel time), the bridge scenario was found to be more suitable and effective than the smart light and status quo scenarios.

Due to the limited financing methods of a Small and Medium-Sized Enterprises (SME), choosing the financing method of this type of enterprises is very important for providing liquidity and profitability, so this research presents a model of financing a small and medium manufacturing enterprises based on factoring. The accounts receivable are based on the company's financial and physical flows with the supply chain components, including the bank and the buyers of its products. In this study, in contrast to traditional financing methods that have been considered without considering the company's position in the supply chain, an attempt has been made to develop a mathematical planning model for financing a small and medium manufacturing enterprise in the supply chain by considering both physical and financial dimensions. And be presented in the context of a holistic and systematic approach. In this research, based on the development-applied approach, the model is presented and in order to solve it, goal programming is used and to cover the uncertainty conditions, interval planning is used. The results of the research show that the financing method is superior to the traditional loan-based financing method in terms of generating profit and achieving the desired liquidity.

In this paper, a model for evaluating electronic services in nonprofit institutions is presented. The idea of this model was due to a vacuum of research in this field. Regarding this issue, independent variables have been extracted from the perspective of members of the research community for the evaluation of electronic services based on inductive method and fundamental conceptualization theory. These variables include governance issues, tools, and customers.Indicators for measuring two variables of government and a measurable tool refer to financial systems and based on cost accounting methodology. However, it was not possible to determine the amount (rials) of the customer variable in this way. Therefore, a process was developed using existing theoretical foundations, including the relative estimation method for accounting, the Delon and McLean evaluation model, and the value engineering and how these two variables influence the management and tools. Then, in order to test the model and development process, the municipality of Tehran decided to evaluate the electronic license of the traffic plan. The result of determining the value of electronic services allows the use of this model in real terms.

Knowing customer behavior patterns, clustering and providing proper services to the customers is one of the most important issues for the banks.In this research, 5 criteria of each customer, including Recency, Frequency, Monetary, Loan and Deferred, were extracted from a bank database during a fiscal year, and then customers were clustered using K-Means algorithm. Then, a multi-objective model of bank service allocation was designed for each of the clusters. The purpose of the designed model was to increase customer satisfaction, reduce costs, and reduce the risk of allocating services. Given the fact that the problem does not have an optimal solution, and each client feature has a probability distribution function, simulation was used to solve the models. To determine the optimal solution, Simulated Annealing algorithm was used to create neighboring solutions and consequently a simulation model was implemented. The results showed a significant improvement in the current situation. In this research, we used Weka and R-Studio software for data mining and Arena for simulation and optimization

Knowing customer behavior patterns, clustering and assigning them is one of the most important purpose for banks. In this research, the five criteria of each customer, including Recency, Frequency, Monetary, Loan and Deferred, were extracted from the bank database during one year, and then clustered using the customer's K-Means algorithm. Then, the multi-objective model of bank service allocation was designed for each of the clusters. The purpose of the designed model was to increase customer satisfaction, reduce costs, and reduce the risk of allocating services. Given the fact that the problem does not have an optimal solution, and each client feature has a probability distribution function, simulation was used to solve it. In order to determine the neighbor optimal solution of the Simulated Anneling algorithm, neighboring solutions were used and a simulation model was implemented. The results showed a significant improvement over the current situation. In this research, we used Weka and R-Studio software for data mining and Arena for simulation for optimization.

This study shows a model for validating electronic services in non-profit institutions. The thought for making this model is rooted in lack of research in this domain. Regarding this issue, the independent variables for validating electronic services was exploited based on induction and the theory of grounded theory. These variables include the issues related to leadership, instruments and costumers. The indexes related to measuring these two variables, leadership and instruments) are measurable referring to financial systems and based on accounting the final prices. But determining the price ( Rial) for the variable of costumers was not possible via this method. So, a process was created to measure and determine the effects of this variable on the other two using the existing theory including the proportional pricing method in accounting, Delon and Meklin model and validation engineering. Following that and for testing the model and the process, the electronic services of giving the license of transportation limitation by Tehran municipality was validated. The results confirmed the possibility of using this model in open world via determining the price of electronic services.

In this research, factors affecting the development of knowledge management (KM) system are identified in different phases of KM cycle at Petrochemical technology and research center of Iranian Petrochemical Company. Then these factors are prioritized. In this research, first all activities of knowledge management cycle phases in mentioned company are identified locally by using a distributed questionnaire among elites. Then identified activities in before phase are prioritized with considering criteria of knowledge management in each phase from its cycle by second questionnaire. For data analyze and activities prioritization, are used from Fizzy Topsis and Analytical network process (ANP), then results of this methods compare each other. Results indicated which activities have the most priority at each phase of KM cycle, and the company must to attend this activities and investment on them for developing of knowledge management.

In many real commercial and administrative issues, relations are often complex, non-routine and are not predictable by conventional methods. Considering the importance of feasibility studies in making decision to start a production activity, forecasting in marketing studies is very important. There are lots of tools and techniques which are used for having an exact prediction, neural networks can be utilized for forecasting with high degrees of accuracy. The purpose of this article is to demonstrate the preference of using neural networks in forecasting nonlinear processes in comparison with conventional techniques and also to increase its accuracy by using economic parameters such as inflation and exchange rates. As a case study, this paper uses the production rate data of PET bottles from 1379 to 1392, then the production rate of 1393 is predicted by using artificial neural networks and nonlinear models. For validating the model, indexes MAPE and MSE obtained from these methods are compared. The result shows the preference of using the neural network for prediction in comparison with time and exponential series techniques, due to the lowest error in forecasting

AlthoughStrengths, Weaknesses, Opportunities and Threats (SWOT) analysis is a suitable tool for identifying effective factors in order to determine the strategies for an organization, but this analysis cannot take into account the importance or preference of the factors. Consequently, SWOT is unable to determine the most appropriate strategy for the organization. Because the factors in SWOT analysis are not independent, the combination of SWOT with the methods such as AHP and TOPSIS cannot solve the problem. Using the ANP which can consider the dependencies within the factors, along with SWOT analysis is able to solve the problem of dependencies, but in real world, there are some other limitations such as budget or labor hours which need to be considered in the problem. Combined ANP and SWOT analysis take into account these mentioned limitations. In this paper, the combination of ANP along with goal programming approach is proposed with SWOT analysis in order to remove these drawbacks. The proposed approach not only considers the real world limitations but also with its distance function, is able to choose the most appropriate alternative. To validate the proposed approach, the model was applied for textile industry in Turkey and Iran. The data for the Turkey, taken from the research which have been done by Yuksel and Dagdeviren. The results show the two countries, apply the same strategy for the textile industry. However, the comparison shows the Iranian experts has the most consistencies in their judgments.

Employee performance appraisal is a systematic and continuous assessment in order to identify necessary areas for growth and improvement of human resources. It is obvious that the performance appraisal methods in different organization levels should be different. These differences are because of job profile and objective in different organization levels. This research tries to find the best way to evaluate the performance of the employees in SAPCO. In addition, the employee performance appraisal methods were prioritized according to assessed person features, assessor features, assessment process, assessment tools and assessment outcomes. The performance appraisal actors in SAPCO were the statistical population in this paper. Scale and couple questionnaires and interviews were the data collecting tools. In order to analyze the data, we used ANP and Fuzzy Topsis. The results showed that MBO and Ranking are the appropriate performance appraisal methods in SAPCO.

Finding the optimized combination of new student entries into universities is always a great challenge for higher education centers. This problem has known as a complicated optimization problem theoretically. In this paper, a systematic approach is developed using a mathematical model to propose the desirable rate of new entries at Allameh Tabataba’i University Business School (ATUBS). Data was collected from several sources of the ATUBS to form the mathematical model. In order to compatible with the reality, the fuzzy logic was utilized because of existence of some qualitative parameters. The results show the satisfactory level is not in a suitable level not only in educational facilities but also for service units in some area in ATUBS. ATUBS needs to revise the student's entries policy to consist with the reality.

Providing wider variety of products often leads to higher complexity in the manufacturing and business system. Finding appropriate methods and techniques to manage these difficulties is going to be an attractive topic for researchers in operations management. By adopting a qualitative approach we have investigated the product variety management in the apparel supply chain. The main contributions of this research are as follow: (1) identification and assortment of dimensions of product variety in the apparel products, (2) developing variety reduction model along the apparel supply chain, and (3) introducing a descriptive framework to fill the variety gaps, in different levels of decision making.

Mathematical models have the potential to provide a cost-effective، objective، and flexible approach to assessing management decisions، particularly when these decisions are strategic alternatives. In some instances، mathematical model is the only means available for evaluating and testing alternatives. However، in order for this potential to be realized، models must be valid for the application and must provide results that are credible and reliable. The process of ensuring validity، credibility، and reliability typically consists of three elements: verification، validation، and calibration. Model verification، validation and calibration are essential tasks for the development of the models that can be used to make predictions with quantified confidence. Quantifying the confidence and predictive accuracy of model provides the decision-maker with the information necessary for making high-consequence decisions. There appears to be little uniformity in the definition of each of these three process elements. There also appears to be a lack of consensus among model developers and model users، regarding the actions required to carry out each process element and the division of responsibilities between the two groups. This paper attempts to provide mathematical model developers and users with a framework for verification، validation and calibration of these models. Furthermore، each process element is clearly defined as is the role of model developers and model users. In view of the increasingly important role that models play in the evaluation of alternatives، and in view of the significant levels of effort required to conduct these evaluations، it is important that a systematic procedure for the verification، validation and calibration of mathematical models be clearly defined and understood by both model developers and model users.