m.r. fathi

The main purpose of this research is the customer experience management model in personal insurance.

To achieve this goal, first the effective factors and indicators affecting the management of customer experience in personal insurance based on the data model of the foundation are identified and then these factors and indicators are categorized. Case study and semi-structured interviews with experts and professors led to the development of research model criteria. Based on the interviews conducted and reviewing previous studies, the factors affecting human resource development strategies in domestic and foreign categories have been identified.

A total of 17 categories and 104 concepts were identified and extracted, and finally the consequences, results and results of strategies or actions are reactions. In total, the model obtained in the present study consists of 6 dimensions, 17 components and 104 indicators, respectively. In this study, the category of "customer experience management model in personal insurance" is mentioned in almost all interviews and plays a pivotal role. Causal conditions In the proposed model, the six central codes of "time management", "cost management", "leisure management", "appropriate decision making", "welfare and comfort" and "social conditions" are considered as causal conditions.

The final finding and achievement of the present study is a relatively comprehensive and complete model based on the customer experience management model in personal insurance and is more appropriate than other models provided by experts in that they have been developed for non-service communities.

The purpose of this study is to investigate the impact of brand community on brand loyalty through the mediation of Customer Identification and Customer Brand Engagement. The present research is a descriptive-correlational and applied study. The statistical population is the customers of Hyperstar store and the sample size was calculated as 374 customers according to Cocaran's formula. Questionnaire was used to evaluate the research hypotheses and the relationships between variables. To evaluate the validity of the questionnaire, content validity method was used and to determine the reliability, Cronbach's alpha was used. In this research, to investigate the relationships and hypotheses, structural equation modeling and partial least squares methods were calculated using smartPLS software. The findings confirm all the hypotheses, in other words, the brand community has a positive and significant effect on brand loyalty through the mediation of Customer Identification and Customer Brand Engagement.

The main purpose of this study was to investigate the relationship between transformational leadership, project participation, project abandonment and employee perceptions of employer safety commitments. This study is applied in terms of purpose. Also, the present research is in the nature of descriptive correlational research in terms of nature and method. The statistical population in this study is managers and staff active in oil and gas projects. Accordingly, random sampling was used in this study. The sample size of this study is 384 according to Morgan table. The data collection tools used in this study included Ding et al (2017) and Mullen et al (2017) questionnaires. The items in these questionnaires were designed based on a five-point Likert scale. Confirmatory factor analysis was used to analyze the findings of the present study. The findings of the study showed that from the viewpoint of the respondents, transformational leadership had a significant impact on project participation; desire to quit the project and employee perception of employer safety commitment. In fact, this research shows that changes in project participation levels, project abandonment, and employee perceptions of employer safety commitment can be explained and interpreted by transformational leadership and leadership styles, and organization managers should pay more attention to use and Implement transformational leadership style.

Predicting corporate financial distress is one of the main issues facing managers, which can significantly contribute to companies' success and survival because corporate managers can be informed of financial distress and bankruptcy by providing warning and timely signals. Therefore, it is possible to avoid wasting resources and damages due to bankruptcy through proper management. This study's main purpose was to select the financial variables affecting the prediction of financial distress of companies listed on the Tehran Stock Exchange and then to predict financial distress using the ANN method. Therefore, first, 106 companies were selected by the simple random sampling method. Their financial data were extracted during 2007-2020. The relationship between variables was examined through the Pearson correlation test. Out of 34 financial ratios, 24 ratios with a significant relationship were selected. Finally, the ANN method was used to predict corporate financial distress, in which the financial distressfulness or non-distressfulness of 103 companies was correctly predicted. Comparing the prediction made by the ANN method with the actual values of the dependent variable in 2020, it was found that this method correctly predicted the corporate financial distress with a confidence level of 97%.

Competitiveness is one of the most important business concerns and activities in a dynamic and competitive environment today. The competitiveness of economies depends on the competitiveness of their companies. The main objective of this research is to identify and prioritize the effective factors on the competitiveness of the rubber industry. The present research is exploratory from the point of view of orientation, applied and from the target dimension. In this study, the factors influencing the competitiveness of the rubber industry were extracted using a background review and interview with experts. The statistical population of this study is the experts in the rubber industry. 15 experts were selected using available judgment sampling. The stages of this research are: extracting effective factors on the competitiveness of the rubber industry by employing interviews and reviewing the background, screening the research factors using binomial test, prioritizing research criteria with DEMATEL and EDAS techniques. Based on the results of the research, the order of priority of the research factors is the necessary industrial infrastructure, productivity, product quality, tax support, banking and customs.

Nowadays, due to too much focus on the development and market complexity and economic constraints, optimal use of available resources and knowledge to create value activities for customers and to timely response to the demands of customers in different market segments is the activity has become inevitable and has forced organizations by eliminating the traditional structures and working methods, by increasing the level of customer satisfaction, maintain its share in market. These factors make the move organizations toward lean manufacturing. Value stream mapping is a tool for improving quality and implementation of Lean Manufacturing base, is very important and basic that as one of the most common methods of analysis systems for detect and remove different wastes to be used in operating activities and support. In this study, production status a manufacturing company by using value stream mapping and change the status of production planning has been guided towards lean manufacturing and results of employing Value stream mapping methods by ARENA software is simulated. Results of this study represents is impact of the application of this method in improving the key indicators of industrial production the studied.

In today's world, organizations need to reduce their costs and improve their productivity to survive. An effort that can be made to increase productivity is the performance of supply chain management. Sustainability in the supply chain, which takes into account the serious environmental challenges, prevents the production of any kind of pollution from human life by producing green products. The main purpose of this paper is to provide a Multi-Stage Data Envelopment Model to Assess the Sustainable Supply Chain Network of Rubber Producing Companies. The methodology of this research is analytical-descriptive and in terms of purpose is applied. One of the techniques that can be used to evaluate the performance of a stable supplier is data envelopment analysis. The research community in this study is 10 rubber companies whose performance has been evaluated over the past three years in 2013, 2014 and 2015. Based on the results, in 2013, Simorgh and Pars tires were ranked one, in 2014, Barez Tire and Pars Rubber ranked one, and in 2015, Barez Tire, Kavir Tire, Pars Tire and Iran Tire ranked one.

the main objective of this research is the future scenario of the country's rubber industry based on soft systems methodology. In this study, using two methods of futures studies, structural analysis and scenario analysis, firstly, identifying the key factors affecting the future of the rubber industry of the country and then developing future scenarios. Became subsequently, using one of the research tools that includes soft systems methodology, these scenarios will become Better. The preliminary data of the research were collected using interviews with the managers and experts of the country's rubber industry and reviewing the literature. The questionnaire was analyzed using MIC- MAC software. Among the 24 key factors extracted, by reviewing the literature and interviewing experts, key factors entered the checklist questionnaire and the 13 key factors according to their assumptions related to them at 0.05, were selected according to experts' opinion. Based on the results of the research, two factors of production technology and performance the value chain of petrochemical industries were considered as the affecting variables in the future of country's rubber industry. Finally, four scenarios were presented.

The purpose of this research is to provide a model and model for selecting a sustainable supplier. The researcher, through library studies, interviews with experts and experts in tire producing companies, and preparing a questionnaire to identify the factors that affect this relationship. Indicators that influence the selection of sustainable supplier selection in this research are financial position and market share, proposed price, timely delivery of goods, recycling rates, the use of clean technologies, contamination, the number of trained staff and employee satisfaction, and Customers In this research, weighing these indices was determined by comparing the fuzzy pair between these indices and using the fuzzy hierarchical process analysis method. In order to accurately determine the weight of the indices, Shannon Entropy method was used. Finally, the weights obtained from these two methods were combined and the final weight was obtained. These weights were used in the Interval TOPSIS method. Then the companies were ranked according to the coefficient of closeness obtained by the distance tops method, and the top company was selected.

Industrial wastewater containing thiocyanate causes increased pollution in rivers and seas. In this research, magnetic nano particles modified by chitosan-Fe (III) used as an efficient adsorbent for removal of thiocyanate from aqueous solutions. Removal percentage of thiocyanate by modified magnetic nanoparticels is more than magnetic non- modified nano particles. The effects of different parameters such as pH , amount of adsorbent, time of stirring and temperature on the removal of thiocyanate has been investigated . Maximum removal percentage (96.7%) were obtained at pH= 4 , 0.03g of adsorbent in 10 min. The results showed that maximum adsorption capacity of the adsorbent is 88 mgg-1. Kinetics isotherms and thermodynamic parameters were studied. The experimental data were correlated reasonably well by Langmuir adsorption isotherm. Kinetic data were well fitted by a pseudo-second order model.Ethanol :aceton solution was applied to regenerate the adsorbent.The results showed that adsorbent could retain its high efficiency after several times of desorption and regeneration. This method is simple, cheap and it could efficiently remove thiocyanate from aqueous solutions .