درخت حوزه‌های تخصصی

The purpose of this research is to Developing a dynamic model for the impact of Servicescape on customer experience in the hotel industry. The present study is a mixed research method. In the qualitative part, the strategy is qualitative content analysis and in the quantitative part, it is applied in terms of purpose and descriptive-survey in terms of research method. To gather information in the qualitative section a collection of articles, books and thesis has been used systematically and in the quantitative part, a standard questionnaire was used to collect information. 700 loyal customers of five-star hotels in Northwest of Iran were selected for the study. A clustered sampling method was used to select statistical sample. In qualitative part, To analyze the data of this research, special content analysis processes including open coding,, axial coding were used to emerge concepts and categories. In the quantitative part, the research hypotheses were tested using structural equation modeling technique. The results of the research showed that the substantive staging and communicative staging have a positive impact on the customer experience and the effect of communicative staging on customer experience at different stages of the relationship life cycle is different.

Online social media is an important innovation that has attracted individuals and companies. The purpose of this study is to "develop an online social media marketing model about consumer buying behavior". This utilizes a mixed-method (qualitative and quantitative). This study uses the research literature to extract the indicators, then, finalizes them by the Delphi technique in three different rounds. The study develops the qualitative model of the research based on the opinions of 20 experts as well as the application of Interpretive Structural Modelling (ISM) and MICMAC analysis. In the quantitative part, the study uses the Partial Least Squares (PLS) technique to implement SEM, validate, and test the predictive relevance of the initial model. This study applies Cohen's formula and determines 460 individuals as sample. The sampling method is non-probability. Furthermore, the statistical population of the study consists of online social media users from all over Iran. In this study, 9 key factors have been identified, modeled and analyzed. According to the MICMAC analysis results, perceived security (with the highest driving power) is identified as the driving indicator, and value co-creation (with the highest dependence) is identified as the result or target indicator. The ISM based model is validated using SEM and 15 hypotheses were checked using SEM-PLS technique, also all hypotheses except the second hypothesis were confirmed. Finally The findings confirmed Goodness of Fitness and ideal predictive relevance of the model.

Safety policies are implemented in the organizations to reduce occupational accidents and prevent waste of resources. Numerous measures will reduce the failure to implement occupational safety policies. In this research, these factors are identified and ranked.This research is applied and adopts survey as its strategy. The research population consists of 15 Safety managers in Kerman province who are selected through non-random and purposive sampling. Data collection tools are interviews and questionnaires and FMEA technique and integrated approach of AHP and fuzzy TOPSIS are used to analyze the data. Based on the findings, important and effective measures to reduce the failure of safety policies implementation include reducing the change of managers and requiring new managers to implement safety policies, developing scientific programs in accordance with the organization's capabilities.According to the research findings, it is necessary for organizations to pay more attention to creating and strengthening the structure of safety units by carefully planning and changing the approach of managers.

Personality is one of the most important study structures in organizational behavior that can play an important role in predicting human behavior. To describe the differences in personality, emotional, and social behavior, researchers have proposed the theory of five personality factors, known as the Big Five. One of the decisions investors make is to allocate wealth to financial and non-financial assets. The importance of this decision is especially evident in financial assets due to their nature and the need for more knowledge and expertise in this field because the mistakes of investors in this regard can create many risks and challenges for them. The main purpose of this study is to explain the effect of personality traits and demographic features on the risk-taking behavior of investors in the Tehran Stock Exchange. The present research is applied research in terms of goals and descriptive-survey research from the method view. The statistical sample of this research includes 358 investors of the Tehran Stock Exchange during 2019 and 2020. Research data were collected based on Sivarjan's (2018) questionnaire. The results of data analysis using the structural equation modeling method indicate that personality traits including neuroticism, extraversion, openness, agreeableness, and conscientiousness have a positive and significant effect on risk-taking behavior. Still, demographic characteristics including gender, age, marital status, and education do not have a significant effect on risk-taking behavior.

Countries have made significant investments in the last decade to reach the international market of renewable energy. Studies potentially have indicated a beneficial renewable energy market. Accordingly, firms must alter their business model to enter the global market. This research aims to discover strategic factors in international marketing management for new renewable energy products. The community of this research includes experienced managers and experts in the field of renewable wind energy. The analysis is applied in terms of purpose and is of the qualitative-quantitative method. In this study, structural equation modeling and Smart PLS software have been utilized for data analysis. The results indicate that 11 strategic factors could influence the international marketing management for new wind renewable energy products, and their effect is at a significant level. Finally, the research model was analyzed using fuzzy inference system (FIS) and Matlab software.

The aim of present study is to achieve a comprehensive framework in the area of customer experience management in Taban Airline to improve business results. The statistical population was the managers and senior experts of Taban Airline. A sample of 16 people was selected by using a purposeful snowball sampling method and in-depth and a semi-structured interview was performed with them. Data analysis was performed using a 3-step coding method in Nvivo software. Finally, a comprehensive model of customer experience management was presented. A total number of 601 open codes were extracted. After methodological modifications, they turned to 182 open codes or concepts, and in the next step, namely ladder of abstraction, they turned to 38 sub-categories and in the final step, they turned to 14 main categories. Finally present the paradigmatic categories and components form the comprehensive Customer Experience Management (CXM) model.