futures research

Peace education changes behavior and enables adults to avoid conflicts and violence and resolve them peacefully by focusing on indices such as knowledge, skills, and attitudes. University is an important organization that plays a significant role in education and creating sustainable values in society..

The research method was qualitative and according to the quasi-numerical or judgmental approach in the field of futures research methods. The measurement tools included authentic domestic and foreign articles, field studies and documents, and were based on the development of questionnaires in two stages using the Delphi technique. This Delphi Panel methodology consisted of 20 education and communication experts in educational sciences and humanities, and they were selected by the researchers using a judgmental method. The matrix of cross-impact analysis coefficients was used with the help of MICMAC software for structural analysis.

The research findings, including 94 primary codes or indices and 11 components indicated that cultural, environmental, educational, and media factors had the highest effects on cultural intelligence, and thus four scenarios were developed, namely human dignity based on peace education, symbolic and unstable peace education, hegemony or the collapse of the education system, and peace education as the basis of global citizenship education.

Futures research can forecast the future of peace education with the greatest accuracy and the least uncertainty. The future forecast of peaceful education can reduce conflicts at schools, universities, and other educational institutions and lead society towards sustainable growth and development.

This study examines the application of quantum intelligence in simulating futures scenarios and its impact on strategic decision-making. In this regard, a combination of qualitative and quantitative methods has been used to analyze complex data. Quantum intelligence algorithms with the ability to process in parallel and solve complex problems help create more accurate models in predicting future scenarios. The results of the study show that the use of quantum intelligence can provide effective tools for strategic managers to more accurately predict and simulate different futures. Simulation of scenarios based on quantum intelligence can improve strategic decision-making in the face of complexity and uncertainty. Overall, this research showed that quantum intelligence could revolutionize the way strategic scenarios are analyzed and predicted.

Utilizing the capabilities of development sociology and future research together helps to evaluate the results of political, social and other measures in practice. This research aims to show the common capabilities and capacities of development sociology and future research as a science and tool, in such a way that it is possible to find Common routes alignments between the two. To check this alignment, the model of correlation of sciences has been used. According to the findings of this research, the background of sociology of development has grown and evolved in its own way, but it has not been logically connected with future studies. But in connection with it, with future research, from the views of; Traditional to forecasting, exploratory or based on imaging and future-making, whether based on a prescriptive or retrospective approach, by describing the factors of social phenomena in relation to past trends, makes future behaviors more predictable. The present research has tried, by looking at the background of the sociology of development, before the discussions of future studies. To investigate the application of exploratory future research, imaging future research and prescriptive future research in the sociology of development, to reach the desired situation.

Despite the great importance of branding on the growth and development of businesses in the national economy, and its development implications for various industries in the present and future, the statistical data indicate the low efficiency of the road transport industry of this huge scientific capacity, commensurate with the capabilities. The aim of the present study is to explain the consequential factors of the branding model in the freight transportation industry in Iran for future research. This research has an exploratory-applied nature; With interpretive-structural paradigm; a mixed approach of qualitative data-based methods and quantitative method of structural equations is a futuristic approach to the analysis of processes; Using Max QD software and a small phase of structural equations using LISREL software, its statistical population is a combination of elites and experts in the field of freight transport, business management science and the science of the future of research. They were identified and selected by snowball method. Based on the findings of this study, the most important outcome factors of the branding model of businesses in the freight transport industry are: increasing innovation, providing added value, reducing complexity, compensating for price pressure, reducing road traffic, reducing risk, return on investment, increasing satisfaction Customers, differentiation, quantitative and qualitative growth of services, standardization of services, reduction of fuel consumption and, consequently, recognizing these factors and paying attention to them, help managers in strategic planning for the growth and development of businesses related to the freight transport industry and favorable future. .

Both public and private media organizations operate in a highly complex and uncertain environment. The advancement of digital technologies and mobile communications has resulted in fundamental changes in this industry, and anticipated developments in communication technologies, digital convergence, stakeholder participation in value production and distribution, new forms of media consumption, and other issues have made the industry's future direction unclear and complicated. In such a situation, senior executives and media policymakers must find ways to forecast the future and devise strategies to address the opportunities and threats that lie ahead. Many experts have emphasized the significance of future research in media management. emphasized strategic thinking in media managers in the sense of seeing the future and understanding the dynamics of the environment, and they saw the idea of the future as the origin of the media organization's actions and thus the drivers of current actions. As a result, managers try to understand not only what is happening, but also what might happen, has the potential to happen, or will happen in certain circumstances in the future. Among the various methods presented to predict the future, such as "valuable" and "exploratory" or "quantitative", "pseudo-quantitative", and "qualitative", one of the less used methods is the "Morphology Analysis," which analyzes and processes existing and future structures using set theory, topology, and random functions (Mozuni and Jonas 2017). This method identifies a vision of future drivers (Prashar, Tortorella and Fogliatto 2022) and analyzes the possibility of occurrence and its effect on the organization using matrix logic (Krauss, et al. 2022, Miklautsch, Hoffelner and Woschank 2022). Despite its solid theoretical foundations, this method's analytical dimensions have yet to be fully developed. As a result, given the importance of this method in future research studies in general, and future research of media organizations in particular, the current study seeks to identify the method's flaws as well as its theoretical and practical development in the media industry.

To analyze the morphology with a network-fuzzy approach, there are eight steps as follows: 1) defining a problem and formulating it; 2) Determining the future drivers of the media industry; 3) drawing a graph of the effects of propellants; 4) extracting the weight vector of the thrusters; 5) Verbal-fuzzy evaluation of the uncertainty of drivers; 6) Multidimensional matrix drawing; 7) evaluation of the outputs, based on the two factors of the place of occurrence and the degree of proximity to the desired goal; 8) A deeper analysis of the possible answers is suggested. The Dematel model was proposed to draw a graph of the effect of propellants, and a matrix was calculated based on the mathematical relationships of the final step of Dematel to extract the weight vector of the propellants (importance factor of the propellants). In this study, a fuzzy number was used to show the linguistic value of the k-th expert, and the fuzzy average operation was used to combine the k-th expert's fuzzy numbers, and finally, the uncertainty of the drivers was calculated as a fuzzy number. In the final section, the multidimensional morphological matrix was developed and mathematically modeled based on the two elliptic fuzzy vectors described in the verbal-fuzzy evaluation and the center of gravity of the propellant in the media industry. According to the obtained model, the weight of the propellant will increase as the decentralization in the verbal-fuzzy evaluation decreases and the distance of the center of gravity of the propellant in the media industry from the origin point of the coordinates increases.

In this section of the study, an attempt was made to present a numerical example based on five media industry drivers based on the opinions of seven experts. The communication matrix between the drivers was extracted first based on verbal concepts, and the fuzzy matrix was calculated next. The calculations yielded L, M, and U values for two vectors a (lack of concentration in importance factor) and b (lack of concentration in event uncertainty). According to the findings, the second driver has the highest level of concentration, while the first driver has the lowest level of concentration. Finally, the value of V or the weight of each propellant was calculated using equation 9. The weight vector obtained shows that propellants 4, 1, 5, and 2 have the greatest amount of weight. The network-phase morphology matrix of media industry drivers can be extracted further in this study using the diagram below.

As stated in the n article, future studies have been proposed as one of the study trends in the media industry due to the increasing complexities of the environment and the rapid changes in the media industry. Future research is conducted using a variety of methods that are classified according to the nature of the data. One of the less introduced qualitative methods is morphology, which evaluates future drivers based on the qualitative judgment of experts based on the two dimensions of "effect on the future" and "probability of occurrence". Because human speech is composed of two parts, mental and objective, verbal evaluation is challenged by degrees of abstraction and concreteness, resulting in ambiguity in the truth of the meaning. Therefore, verbal evaluations, especially in humanities studies, have multiple states of degrees of truth instead of the dual state of truth-untruthfulness. On the other hand, this method is developed based on the mutual relations of the drivers, which is assumed to be linear in the previous studies of this interaction. Based on this, as discussed in the article, future studies have emerged as one of the study trends in the media industry by using fuzzy logic, the possibility of multiple valuations of degrees of truth, and using the Dematel technique, the possibility of network analysis and non-independence in future engines and analysis of morphology. Future research will take the form of various methods that are classified based on the nature of the data. One of the less introduced qualitative methods is morphology, which evaluates future drivers based on the qualitative judgment of experts based on the two dimensions of "effect on the future" and "probability of occurrence". Because human speech consists of two parts, mental and objective, verbal evaluation is confronted with degrees of abstraction and concreteness, causing ambiguity in the truth of the meaning. At the end of the findings, the proposed model is a kind of applied qualitative classification based on two fuzzy vectors "effect on the future" and "probability of occurrence" and the calculation of two variables "lack of concentration" and "center of gravity" in the evaluation and classification of future drivers in the media industry. Following the theoretical development of the morphology matrix's fuzzy-network mathematical relationships, it was simulated in the MATLAB software environment and tested using a numerical example. The morphology of organizational social media was done through discrete valuation and with a nominal scale in Viravali and Viayalakshmi's (2019) article, and the relationship between the dimensions was not considered, nor was the precedence between the studies done. However, in this article, the valuation was done using a fuzzy and continuous distance scale, and because the studied dimensions were not independent, the relationships between them were studied using network logic, and finally, precedence Propellers were obtained by combining the value of two developed morphology vectors. Furthermore, according to the research findings of Prashar et al. (2022), Krauss et al. (2022), and Miklautsch et al. (2022), the morphological analysis method has a high capability in the typology of all kinds of qualitative concepts and rank classification, which is still applicable after the development of the network-fuzzy model. This feature has been preserved for this method. At the end of the findings, the proposed model is a kind of applied qualitative classification based on two fuzzy vectors "effect on the future" and "probability of occurrence" and the calculation of two variables "lack of concentration" and "center of gravity" in the evaluation and classification of future drivers in the media industry.

Today the financial technology industry(FinTech)is developing more and more than in the past and has attracted the attention of users.In this regard, FinTech startups have tried to expand their activities by attracting users and diversifying the services they can provide.Undoubtedly they will play a more colorful role in the financial system of Iran in the coming years.Therefore, the decision makers in the banking and financial industry of the country need to know the possible future of these startups.The purpose of this research is to investigate the position of fintech start-ups in Iran's financial system in2031and it is of a qualitative and practical type, its statistical population includes experts in the financial field,bank managers, managers of fintech start-ups and politics.The snowball method was used for sampling and15people were selected purposefully and using the analysis of cross effects,influential factors and key components were extracted, then using Scenario Wizard software for structural analysis and checking how these factors affect Also,the extraction of scenario spaces has been used, and finally,4compatible and probable scenarios related to the future of startups in the fintech industry include conquering the territory(complete dominance of startups)competition in conquering the industry(competition of banks and startups)remaining(the lack of acceptance by users and the banking industry of start-ups)and the gradual death of a dream(failure of start-ups)have been extracted and described.After narrating the scenarios and through the findings of the expert panel and summarizing them, an attempt was made to provide strategic recommendations for the managers and policymakers regarding the future of fintech startups.