فهرست مطالب vahideh bafandegan emroozi

The rail transport industry can have good growth and development if it pays more attention to the quality of its services and passenger satisfaction. Despite the importance of quantitative evaluation of passenger train services in the growth of quality of life and performance improvement, limited studies have been conducted in this field. . In this study, an approach for quantitative evaluation of passenger train quality services on a busy route from the perspective of passengers and based on data envelopment analysis is proposed. For this purpose, first, the evaluation criteria of trains were extracted by studying the literature, and then the most important ones were identified based on the opinions of experts in the field of rail transportation. The level of desirability and satisfaction of each of the indicators for 16 types of passenger trains was acquired from the passengers' point of view. Then, to determine the efficiency of passenger trains based on the quality of their services, output-oriented models in terms of efficiency relative to fixed scale (CCR) and variable (BCC) have been used. Finally, based on the Anderson and Peterson model, a comprehensive ranking of passenger trains Presented from the perspective of travelers. The results show that under the assumption of CCR, Saba (normal), Saba (fast), Noor, Zendegi and Parastoo trains have the highest efficiency from the passengers' point of view, and considering the BCC assumption, Fadak, Pardis, and Persian Gulf trains are also included in the total.

Supplier selection of urban train signaling equipment is one of the main problems in urban railways due to the serious impact of this equipment on the safety of travelers. The supplier's selection is a multi-criteria decision-making (MCDM) problem, in which the preferences over criteria are highly dependent on the opinions of decision-makers (DMs). The focus of the present study is to provide an appropriate model of multi-criteria group decision making in a probabilistic setting to effectively combine DMs' judgments. For this purpose, the Bayesian hierarchical model with the best-worst method (BWM) is used to determine the weights of criteria and the Vise Keriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is used to prioritize suppliers. Bayesian BWM aggregates the opinions of all DMs at once, instead of averaging the individual opinions of the DMs that underlie MCDM methods. In this method, the probability of preference of one criterion over one another is calculated using Markov-chain Monte Carlo (MCMC), in addition to the weight of criteria, so that the confidence between pairs of criteria is revealed and ranking of criteria become more certain. Given that the average obtained confidence levels are 0.95, the validity of the Bayesian BWM results is confirmed. For different values of the VIKOR parameter, the third supplier will have the highest rating and the fifth supplier will have the lowest rating. The introduced multi-criteria decision model in this research will help the decision-makers of the urban railway company and other organizations with several suppliers to be able to select the best supplier by considering the relevant criteria.

Commercialization of innovative products in small and medium-sized enterprises (SMEs) faces many challenges. In this study, the factors related to the existing challenges and resolutions are identified with the help of the multi-layer fuzzy cognitive mapping (ML-FCM) method. The most effective criterion is introduced by examining the centrality. Also, the challenges and the existing resolutions to overcome these challenges are specified, and the most effective ones are determined. The present study addresses the practical experience of Sanat Prozheh Toos Company, which operates in the design and production of mechanical noise pollution control equipment (e.g., Silencers). The data is collected based on the organization's documents and experts' opinions. Research findings confirm that among the challenges of commercialization of innovative products associated with the case study, management challenge has the highest degree of effectiveness and centrality; moreover, among the ways of overcoming these challenges, organizational integration has the highest degree of centrality. Thus, the findings provide policy and management suggestions for SMEs policymakers and managers in commercializing advanced technologies.

The problem of selecting the suppliers along with their Economic Order Quantity (EOQ) has always been an important issue in the Newsvendor model. Multiple qualitative and quantitative criteria are needed to be regarded for making a better supplier selection while performing trade-offs among them. An approach that can take all criteria into account in the selection of suppliers has not been developed yet in the Newsvendor model. Multiple criteria decision-making (MCDM) can be leveraged to make trade-offs among multiple criteria.

This study sought to develop a solution to the Newsvendor problem, accounting for the most significant criteria in supplier selection and product reliability so that the total cost of the chain would be minimized in a multi-product and multi-period model with multiple suppliers. This approach adopted the Bayesian Best Worst Method (BWM), which is one of the MCDM methods, to rank the criteria and also implemented the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritize the suppliers. Then, the suppliers' weights were used as the proposed model inputs. The results obtained from Bayesian BWM validated the effectiveness of the presented approach. The objective function was set in a way that a retailer's profit and weight value of products considering the ranking of suppliers were maximized. The goal was to find optimal order quantity allocating to suppliers. To convert the multi-objective model to a single-objective, the Lp-metric method was used.

To evaluate the derived model, a case study with real data in the electronic supply chain was investigated. The developed model for the Newsvendor problem could find the best suppliers by considering a combination of qualitative and quantitative criteria in selecting them. In this research, the real-world case study was considered in the electronics industry, which allowed the researchers to make a better evaluation of the model.

The obtained results indicated that the retailer uses a combination of suppliers in each period for optimal order allocation to profit-maximizing considering product's reliability and the weight value of products.

Ergonomics or engineering of human factors has been formed with the aim of increasing productivity and considering the importance of human health and safety in the workplace. The aim of the present study is to prioritize ergonomic factors affecting job satisfaction of law enforcement personnel.

The present study is applied and descriptive-analytical research. The decision-making team consists of 15 NAJA experts who are aware of human resources issues with at least 20 years of work experience and were selected by snowball method. In this study, the indicators and strategies extracted from the relevant background and texts were first reviewed by experts. In the next step, in order to rank and determine the weight of the identified indicators and strategies, fuzzy sequential analysis method was used. The questionnaires were validated using the opinions of an expert group. Also, reliability was confirmed in the initial questionnaire by calculating Cronbach's alpha (0.92) and in the fuzzy serial chain analysis questionnaire with incompatibility rate less than 0.1.

First, by examining related texts and literature, nineteen strategies for promoting human factor engineering were identified. The experts then selected the six most important strategies for providing personal protective equipment, providing the right work tools, improving work shifts, controlling work pressures, providing uniforms and boots, and creating the right posture at work as the most important strategies.

Due to administrative, financial and time constraints, NAJA can implement the principles of human factor engineering with the aim of increasing the job satisfaction of its employees, thus improving the work shift, providing appropriate uniforms and shoes and providing appropriate tools and equipment as a job.