safar fazli

According to the laws, electronic invoicing is the responsibility of companies providing tax services in Iran. However, the existing uncertainties have caused vagueness in the business environment of the mentioned companies. The main question was ̒How is the business model suitable for each of the upcoming scenarios for tax service providers?̓. This research attempted to provide a practical solution to these problems by adopting a foresight-based approach to business model design. For this purpose, the business model design framework based on foresight was used. Sampling among subject matter experts, was done by judgmental method and 15 experts were selected. In the theoretical stage, a systematic review method, and in the experimental stage, questionnaires were used. The methods, analysis techniques and softwares including PESTEL , binomial test, CRITIC, Fuzzy-VIKOR, GBN, TASCOI, Multi-Mora, Business Model Canvas, Key Success Factors, Road Mapping, Workshop, SPSS 27 and MS-Excel softwares were used  for data analysis. Among the 36 primary drivers obtained from the background and opinions of experts, 11 important drivers and 2 key uncertainties "single/multiple regulation" and "non-economic/economic tariff rate " were extracted. In response to the main research question, four scenarios were formulated, the probable scenario was determined, and the business model and roadmap were designed according to the probable scenario and the scenarios. The results showed that by applying the insights obtained from the use of foresight in business model design, in addition to considering alternative futures and drawing the path of transformation to the desired situation, it is possible to make the business of tax service providers future-oriented through creating a strategic vision.

The purpose of this research is providing a solution to help make better decisions in the ambiguous world of uncertainties. In a world full of uncertainties, researchers invented methods such as scenario planning and robust decision making, and for highly ambiguous environments they tough up fuzzy logic. Today, without a decision support system, decision making will be done relatively slowly. Without considering different scenarios, it is not possible to make robust decisions in the face of numerous large and small uncertainties.

This research is of applied and qualitative type. The data were collected in a documentary and library method from the articles and books available in reliable scientific databases using computer files. The type of data is qualitative and the method of data analysis is thematic analysis.

In robust decision-making, scenarios are used in two ways. In one case, after choosing several alternative decisions, you can write the scenarios that affect them and evaluate the decisions. Otherwise, you can first write different scenarios and then test alternative decisions in those scenarios and choose the optimal decision as the robust decision. Also, fuzzy logic can be used in the form of fuzzy Delphi and other fuzzy calculations in different parts of scenario planning and strategy robustness evaluation.

Originality/Value: 

In this paper, a method was presented according to which a robust decision support system can be developed using the GBN scenario planning method and fuzzy logic. In this method, fuzzy Delphi was used to create scenarios and fuzzy inference system was used to make decisions.

Todays, strategic foresight is known as an important and vital tool in organizations to deal with uncertainty in the future and stability in complex environments. The purpose of this research is to investigate the role of strategic foresight in supply chain performance. For this purpose, the moderating role of strategic flexibility has been used as a moderating factor. The statistical population of this research is all the members of the supply chain of the Iranian automobile industry, and two stages of simple random sampling and stratified sampling proportional to the volume have been used. 136 questionnaires were distributed and finally 125 questionnaires were analyzed. To test the 5 main hypotheses, structural equation modeling method based on variance (partial least square fan) and path analysis was used. The results and analysis of outputs showed that strategic flexibility and shared value creation have a positive and significant effect on supply chain performance. Among the indicators of strategic foresight, only formal organization has a negative effect on strategic flexibility, and the rest of the indicators have a positive effect. Strategic flexibility also has a positive and significant effect on the creation of shared value. The results of this research lead supply chain members to a correct understanding of the impact of strategic foresight on supply chain performance in order to improve future decisions.

Considering the importance and position of rural tourism and creative approach in the development of the future rural of Iran, and also considering the lack of a study in the field of Creativity-Based Rural Tourism based on a future-oriented perspective; How to conduct such a research is questionable. Therefore, the main goal of article is to present the framework of the proposed model for the strategic foresight of the development of Iran's Creativity-Based Rural Tourism in horizon of 2045.

This article based on the purpose, is developmental and applied type and is among qualitative, interpretive, exploratory, inductive, survey and descriptive researches. The statistical population includes literature related to the research title published from 2000 to 2020. Information sampling method and representative sampling method were used. The statistical sample consists of 40 studies. To collectting data and information, the survey and qualitative trend extrapolation methods were used, and meta-analysis method was used for analysis.

The proposed model consisting of 3 stages. The input phase is intellectual and software in nature and with the purpose of preparation. The intellectualization stage includes knowledge acquisition, integration and intellectualization, and finally creation as an output that includes two tangible products and intangible.

In the mentioned proposed model, the intended platform for the realization of the model is a collaborative, networked, flexible and sliding platform, creativity-oriented and based on continuous education (pluralism and connoisseurship), and the factor of imagination and creativity plays a prominent role in design and implementation.

One of the basic goals of development is to achieve social welfare for all, and creating a platform for suitable environment for business and employment in any country are crucial factors in driving economic growth, prosperity and ultimately increasing the economic and social welfare of the population. Given the instrumental role of employment in the realization of social well-being, this research firstly aims to empirically identify and define the factors influencing employment and well-being. This research uses a documentary method and semi-structured interviews with experts and specialists in the field of employment and well-being in the Ministry of Labor, Cooperation and social Welfare. In the second step, after counting the factors and key components affecting the future of employment and prosperity of the country, these factors were arranged within a mutual matrix and presented to experts, and then using Micmac software (MIC MAC) the direct and indirect effects of variables on each other were measured. Finally, the research showed that economic structure variables, investment, business environment, welfare system and social justice as two-dimensional variables, policymaking variables, international relations, laws and regulations and banking system as influencing variables, educational system variables and banking system as regulatory variables, variables of the payment system and human resources were recognized as dependent variables, and the variables of the educational system, cultural system, and technology were recognized as independent variables.
Based on the degree of influence and effectiveness of the variables, the priority of policy variables, economic structure, investment, international relations, laws and regulations, business environment, banking system, welfare system, social justice and education system were the most important key drivers affecting the employment and social welfare of the country.

The development of green entrepreneurship as an emerging entrepreneurial revolution is an effective factor in reducing environmental pollution, using the least facilities and gaining the most productivity in doing green business. Therefore, the purpose of this research is to design a green entrepreneurship development model in the field of urban waste management to use this environmental problem as a source of opportunity and turn this environmental and social risk into social values and economic profit. This research is a fundamental in term of purpose and a qualitative-data-based (systematic) research in term of data collection. After selecting 15 owners of urban waste management business, city managers and experts in this field, data was collected by purposeful sampling method and semi-structured interview. Then, data was analyzed in three stages of open, axial and selective coding, and finally 117 primary conceptual categories from open coding, 38 categories from axial coding and 16 main factors from selective coding were identified. The results emphasize that the axial category is the development of green entrepreneurship, which is formed based on causal factors (such as personal and occupational characteristics), field factors (such as institutional, infrastructural, environmental, technology and innovation factors) and intervening factors (such as economic, political, legal and socio-cultural and educational factors). And supportive, corrective, executive and structural strategies can lead to three categories of economic, social and environmental consequences or in other words to the sustainable development. These findings help managers, planners and policy makers in the field of waste management and green entrepreneurship development in creating value (competitive advantage and wealth) and realizing more sustainable futures.

The aim of this study is to investigate the effect of corporate social marketing characteristics and compliance with ethical principles on the intention to change consumer behavior. Hence, the effect of CSM attributes and Ethical issues observation in social marketing campaigns on consumer’s behavior change intention have been investigated in present study. Meanwhile, the mediating role of attitude has been taken into consideration too. Hence, at first via literature review, ethical issues observation and CSM attributes factors along with their dimensions were identified and the relationship between them and consumer’s behavior change intention with the mediating role of attitude were hypothesized. Then the Representatives of Karaj insurance companies were selected as the statistical community and 95 questionnaires using the cluster sampling method collected. The causal relationships between variables were tested employing a partial least squares-based structural equation model in smart PLS 3 and a hierarchical model was presented. Results show that CSM attributes and ethical issues observation influence a consumer’s behavior change intention, respectively indirectly with the mediating role of attitude and directly. In addition, in terms of assigning priority to management-oriented measures relative to the results IPMA analysis, the factor ‘ethical issues observation’ has more importance that in designing CSM program strategies must be take into consideration. This study demonstrates that CSM attributes and ethical issues observation factors result in the intended prosocial behavior adoption and more corporate benefits creation. Presented framework provides managers with further insight into how and why the company can generate social and corporate benefits through CSM.

With the increase in environmental problems and the world's need to achieve sustainable development, a new subfield of entrepreneurship has emerged, known as green entrepreneurship. Given the novelty and early stage of the literature in this field, the current research aims to analyze studies in green entrepreneurship using indicators of scientific measurement. This study contributes to a deeper understanding of the topic of green entrepreneurship.

This study employed a Scientometrics approach, descriptive analysis, content analysis, and systematic review. To address the research questions, electronic databases such as Scopus, Science Direct, and Emerald from 2000 to 2022 were utilized. Subsequently, all descriptive and analytical studies were scrutinized. The systematic review involved inclusion and exclusion criteria to filter relevant articles for analysis. The review framework adhered to the PRISMA checklist, comprising 4 stages (Identification, Screening, Eligibility, and Inclusion). Following the application of evaluation criteria, 171 articles were analyzed.

The analysis shows an upward trend in published articles on green entrepreneurship. It was found that most of the studies were quantitative and conducted using the case study method. Another interesting discovery is the increasing popularity of terms related to green entrepreneurship in recent years, such as green innovation, green and circular economy, and the prevalence of green and institutional innovation theories. The findings revealed that England and China have the highest co-authorship in green entrepreneurship studies. Among the identified factors, institutional and political factors have garnered the most attention from researchers.

The increasing trend of studies in the field of green entrepreneurship, particularly in recent years, can be attributed to the rising needs of societies, resource scarcity, escalating environmental and employment issues, and the growing interest of researchers in environmental and entrepreneurial studies. This surge has led governments to support green businesses. Analysis results indicate that terms like sustainable development, sustainability, and entrepreneurship, which rank at the top, reflect the extensive research conducted in these areas. In contrast, fourth in terms of research volume, indicating a relative scarcity of studies in this specific field. Consequently, further research, especially in green entrepreneurship, requires time. Moreover, research findings from various countries on green entrepreneurship reveal that the majority of research contributions come from developed nations like England, China, and the United States, which exhibit a significant focus on this subject. Additionally, the most cited journals in this research predominantly feature authors from developed countries. The results also highlight that researchers have shown more interest in quantitative and qualitative methods individually, while the combined research method, despite its strengths, has not garnered much attention in this domain. Furthermore, the theories introduced in this research have been long-standing in entrepreneurship but are relatively new in the context of green entrepreneurship. Notably, theories such as innovation and institutionalism have received considerable attention, with the institutional approach emphasizing the importance of a conducive institutional environment for the advancement of green entrepreneurship. Consequently, institutional reforms are essential to enable institutions to support entrepreneurship as a driver of development. The study also identifies factors influencing the progress of green entrepreneurship, potentially opening up new avenues for future scientific exploration. These research findings will aid upcoming researchers in pinpointing gaps in the field, thereby saving time and resources by avoiding redundant issues. By addressing these research gaps, researchers can significantly contribute to the decision-making processes of policymakers and planners

The purpose of this study is to investigate the effect of abusive supervision on employee silence and the impact of the variables of organizational policy perception and leader-follower exchange on their relationships. In fact, in this study, we are looking for the fact that these factors can have a significant impact on employee silence. The method of data collection is through a questionnaire, the time horizon of the research is cross-sectional and the purpose of the research is descriptive-analytical, as well as the research strategy is survey and the research approach is deductive, the philosophy of research is the paradigm of positivism and the orientation of research is applied and, in the end, the type of research is quantitative. 200 questionnaires were distributed among the municipalities of Alborz province, of which 184 questionnaires were flawless and usable. Also, partial least squares and structural equations were used to test the hypotheses. Based on the results obtained, abusive supervision has a negative and significant effect on employee silence, perception of organizational policies as a mediating variable between abusive supervision and employee silence has had a negative and significant effect. Also, leader-follower exchange has a positive and significant effect on employee silence, and finally, leader-follower exchange does not have a moderating effect. Based on the findings of the study, our suggestion to the authorities in municipalities is that by observing the stated cases, they can reduce employee silence in the organization.

The existence of uncertainties, complexities, and ambiguity is one of the structural features of the tobacco industry for the country's planners in the current era. Traditional planning and strategy tools are no longer appropriate in such a situation. Therefore, the aim of the current research is environmental scanning of the factors affecting the strategic foresight of the tobacco industry in Iran. In fact, this research seeks to answer the question of which environmental factors can be effective in achieving the desired future of the Iranian tobacco industry. Environmental scanning is one of the methods of strategic foresight which is to identify, understand, evaluate, and prioritize responses to environmental issues and changes. The purpose of environmental scanning is to give a timely warning to the decision-makers so that they have enough time to react appropriately. The current research is pragmatic in terms of philosophical basis, exploratory in terms of purpose, and applied-development in terms of orientation. The theoretical community of the research is experts and senior managers of the tobacco industry and academic experts selected by judgmental sampling. To scan the environmental factors affecting the strategic foresight of the tobacco industry, in the first step, 66 environmental factors were counted through a systematic review of the research background using the Meta-synthesis method and interviews with industry experts, and then the most important ones were identified using the Delphi method. The 28 screened drivers of the future of Iran's tobacco industry were categorized into economic, individual, and psychological, smuggling, technological, political and legal, social, governance, environmental, health, and marketing groups.

Market sales forecasting has a special role in the analysis of marketing opportunities. Along the same line, sales forecasting plays an important role in the planning of different departments of an organization

Accordingly, the main goal of this research is to use one of the new tools in the field of machine learning (the meta-learning method) to predict the number of sales with a case study. Aluminum is sold in the Iran Mercantile Exchange.

The current research is included in the category of applied research and the research data were collected using secondary data sources. The data available in the weekly reports published on the official website of the Iran Mercantile Exchange Organization has been used for analysis. The steps of conducting the research are based on the principles of prediction and using the meta-learning approach.

The findings of the current research show how to use the meta-learning method to predict the amount of sales and estimate the demand for aluminum in the Iranian Mercantile Exchange. The model is presented using the meta-learning method based on 4 basic prediction methods of the neural network, ARIMA, regression, and exponential smoothing in line with time series data related to aluminum sales in the Iran Mercantile Exchange (including 344 time periods from 2015 to 2022).

Examining the accuracy of the results of using the meta-learning method to predict sales has shown the superiority of this method compared to four other selected prediction methods. In this research, three stages of validation were conducted to verify the results obtained, and in the results of all three validation samples, the superiority of the accuracy of the meta-learning method was confirmed. The capability of this method to solve the prediction problem is one of the capabilities of using artificial intelligence tools in solving different management problems. As a result, the meta-learning method has been introduced to marketing managers and researchers as a powerful tool in the field of sales forecasting.

One of the basic goals of development is to achieve universal social welfare and the existence of social welfare in any society is considered as one of the most important characteristics of the development of that society and the reproducer of its development. Laying the groundwork for creating a suitable business and employment environment in any country is one of the important factors in creating economic growth and prosperity and ultimately increasing the economic and social welfare of the people. Therefore, considering the important role that employment can play in realizing the concept of social welfare, in the present study, attempts have been made to identify and rank the key factors and components affecting the employment and social welfare status in Iran.

In this study, in order to identify and accurately define the components affecting employment and welfare, the documentary method and semi-structured interviews were conducted with the experts and specialists of the field of employment and welfare working in the Ministry of Cooperatives, Labor, and Social Welfare. Hierarchy factorization (AHP) and Expert Choice software have been used.

The results show that the investment sub-criterion with a relative weight of 0.115 has the highest priority, and then the sub-criteria respectively are policy-making, banking system, production, and business environment, laws. Then regulations, tax system, international relations, economic indicators, payment system, insurance and social security, justice and equality, manpower, domestic technologies, culture, foreign technologies, and education system were also the sub-criteria identified in the study.

The most important and key factor that can affect the employment and welfare in the country is the concept of investment. In economic theories, investment is known as the engine of economic growth, and is necessary for economic and social development, and it is one of the most important pillars in the growth and development of production units and enterprises.

The uniqueness of futures studies epistemology, the nascent nature of transdisciplinary disciplines and the lack of literature in the field of its methodology, has led to a lack of proper integration in this field. For this reason, futures studies methodology, like the field itself, has undergone many changes in the last two decades. Due to this serious weakness, the present study seeks to examine the methodology and construction of a desirable and efficient research design tailored to the growing needs of futures studies to prevent confusion among researchers. Major scientific studies in the field of futures studies methodology focus on distinct methods and their implementation; While methodology in futures studies is not an end in itself, it is used to guide appropriate approaches to mapping reality, that is, the future. In this article, with a focus on descriptive-analytical methodology, a systematic study for the development of research methodology based on the research onion model is conducted and the relationship and adaptation of this model for future research are examined. The present article outlines and explains nine stages of methodological development and construction of a research design for future studies, which begins with the definition of a philosophical position and gradually leads to the construction of a research design.

 Social security and, accordingly, the mental image of tourist destinations is one of the main conditions of every tourist destination, which is definitely checked by tourists prior to traveling and then decide where to travel. The present study was conducted with the aim of investigating the impact of social security and the image tourists of destinations on the attractiveness of urban tourism destinations.

 The present research is of applied type in terms of purpose and is of descriptive-analytical type in terms of method. Data collection was done via library and field approach. The statistical population of the study consisted of incoming tourists to Tehran, but due to the lack of accurate statistics on the number of incoming tourists, in order to determine the sample size, Cochran's formula was used for the unlimited population and the sample size was estimated to be 384 people. The tool for data collection was a researcher-made questionnaire, whose reliability was checked and confirmed by compound reliability and Cronbach's alpha, and validity by two methods, face validity and divergent validity. SPSS and Amos were used to analyze the data.

 The research findings showed that social security has a positive and significant impact on tourists' mental image of tourist destinations, as well as the attractiveness of tourist destinations. Given the value of the obtained path coefficient, the variable of social security projects 33.6% of the variance of the mental image of destinations, and 39.6% of the variance of the attractiveness of tourist destinations. Other findings of the research pointed to the positive and significant impact of the mental image of tourist destinations on the attractiveness of tourist destinations. It might be argued that the mental image of tourist destinations could explain 23% of the variance of the attractiveness variable of tourist destinations.

One of the main concerns of developing countries, is to be on the path of development. Accordingly, the existence of strong laws can increase the cohesion of society. Currently, Iranian tobacco industry, one of the oldest industries in Iran, is in an aura of ambiguity and complexity. Growth in unbalanced production and consumption, lack of accountability, corruption and lack of rule of law are among the challenges  of this industry. In this regard, the purpose of this study is to identify the opportunities and challenges of this industry by identifying the drivers, and uncertainties and formulating the possible scenarios. The orientation of the present research is applied developmental, the research approach is inductive deductive cycle, and the research strategy is explantory, descriptive and explantory survey. The data collection methods used, were desk research, questionnaries and panel of experts, and sampling method was purposful and accessible, Mick mac tools were applied to analyze the data and senarios were developed using experts opinion. The two drivers of "political and economic variables" and "good governance" were indentified for the industry. Accountability, transparency, adherence to the law, respect for human rights and moral behavior were also identified as the uncertainties in this industry. Finally scenarios of black swan or lost paradise of multinational companies, health society waiting for good governance, tobacco industry deprived of political and economic blessings and green society, were Iran is determined. a perfect example of a country with tobacco control policy and hence, the green society scenario was selected as the fovorable scenario.

Today, due to the rapid advances in science and technology, the ever-changing needs and demands of customers, the environment of organizations has become more dynamic, uncertain and complex. In fact, these changes have led to an era called uncertainty. To cope with uncertainty and shape uncertain environments, researchers generally agree that organizations need dynamic capabilities. However, limited studies have been conducted to develop these capabilities so far. This study addresses this gap and introduces strategic foresight as an important antecedent for the development of dynamic capabilities and formulating long-term strategies and policies in conditions of environmental uncertainty. The present study is descriptive from purpose dimension, applied from audience dimension  and in terms of data collection method, is correlation. The unit of analysis and the statistical population in the study are the Management and planning organizations of the country’s provinces, which were selected on a simple random sampling method. The collected data were analyzed using structural equation modeling and Smart PLS software. The results indicate that strategic foresight capabilities have a significant role in promoting and improving strategic flexibility, decision rationality and ambidexterity. In addition, the findings confirmed the moderating role of environmental uncertainty in relationship between strategic foresight and the mentioned dynamic capabilities. The study also found that the strategic foresight is the basic antecedent of dynamic capabilities and is one of the most effective fields of study for policy-making, dealing with uncertainties and the resulting challenges in organizations.

The tourism industry is one of the ten most influential industries in economic development in most countries. To this end, major research from various perspectives on this industry has been conducted and is ongoing at all international, national and regional levels. One of these areas of research that plays an important role in micro and macro policy making of decision makers is the issue of ranking different regions. In this research, the provinces of the country are ranked based on operational indicators. These indicators have been developed in this research by studying the samples of valid researches, interviews, field researches and valid national statistics of the country. The result of this identification was 18 operational and performance indicators whose information was accessible and validated in the country. It should be noted that in this study to develop tourism indicators, a wider range of well-known literature called tourism and travel (T&T) has been considered. After identifying the indicators that can be a valid reference for future research, the provinces are ranked by two multi-criteria decision-making tools, TOPSIS and Macbeth. These algorithms are developed in the MATLAB programming environment. Finally, the result of the two methods was that the algorithms confirm each other's ranking in more than 90% of cases. In addition, the provinces of Tehran, Mazandaran and Khorasan Razavi have the first to third places.

Today, innovation, performance improvement and maintaining competitive advantage are the main goals of knowledge-based companies and management innovation can play a significant role in achieving these goals. In this context, the purpose of this study is to achieve different mental patterns of managers towards management innovation in knowledge-based companies and to identify key factors resulting from the explanation of these mental patterns. This research is paradigmatic, interpretive and positivist and based on the purpose of applied research, According to the purpose of the present study, the combined Q method was used to perform it. The participants of this research are managers in knowledge-based companies and their selection was based on their expertise and close relationship with the research topic. Thus, 20 managers with the mentioned characteristics were selected in order to sort the Q ranking table through purposive sampling, which is expected to have more diverse mindsets. In the next step, after sorting the factors in the form of Q cards on the Q ranking table, the obtained data were processed and analyzed by SPSS software. The results of this study show six different subjective patterns resulting from scoring participants' Q options, which Accordingly 27 factors include; Organizational Strategy, Employee Ability, Higher Education Workforce, Partnership, Information and Communication Technology Systems, Market Focus, Community Wealth, Senior Management Commitment, Managerial Education, Transformational Leadership, Tireless Leadership, Formalization, Organizational Policy, Knowledge Management, Organizational learning, absorption capacity, perceptibility, innovative culture, human resources, competitive pressure, rapid technological change, environmental dynamics, government effectiveness, senior management participation, managers 'attitudes toward innovation, managers' personality traits and strategic leadership. are the result of explaining these mental patterns.

Medical Device Industry (MDI) has a special role in the health and economy of the country, but scattered and little domestic researches are devoted to it. This study was conducted with the aim of comprehensively identifying the factors, drivers, and key uncertainties affecting MDI and mapping its future scenarios; Because it is the necessity of programming to support domestic production of medical devices and remove its barriers.

The research was conducted by a similar to Schwartz's critical uncertainty scenario method. By interviews and questionnaire tools in three Delphi rounds, required data were gathered and encoded by qualitative method. Here, the related experts were selected by snowball technique in a purposeful way until the stage of saturation of opinions.

In this paper, the main drivers affecting the next 20 years of the country's MDI were obtained. By identifying the three main axes; the lifting of the (economic) sanctions of US, the growth of R&D in companies, and the reduction of economic corruption, among the key drivers, based on their high importance and uncertainty, five scenarios; Prosperity, Dependence, Hope, Resistance, and Destruction were written.

Future scenarios for the technology-based industries such as MDI show the importance of the supportive requirements for the R&D pillar. In these scenarios, the continuation of economic sanctions increases the cost of economic activities in the industry and the reduction of economic corruption is faced with considerable uncertainty. Therefore, the three factors are the drivers for desired future scenarios of the MDI up to 2040.

This study sought to design a framework for teaching foresight to top managers of governmental organizations in the Islamic Republic of Iran. First, the research literature in three areas of "management of governmental organizations", "foresight" and "teaching foresight" was reviewed. Then, using the "Grounded Theory" method and using the "in-depth interview" tool, first-hand data were collected. This data in three different phases, through "open coding, axial coding and selective coding", were analyzed. Based on the research findings, a general framework for teaching foresight to top managers of Iranian governmental organizations was presented in which in addition to the category of foresight education as a axial category, other categories related to this field such as causal conditions, contextual conditions, intervening conditions, strategies and consequences were also introduced. Therefore, this macro framework can be used as a general model for teaching foresight to top managers of governmental organizations in the Islamic Republic of Iran.

This article aimed at promoting banking industry performance by combining capabilities of knowledge absorptive capacity and corporate foresight in organizations, as well as its effects on innovation and strategic decision-making. Initially, introducing knowledge absorptive capacity and corporate foresight, different dimensions of the construct are mentioned. Then, the relationship between knowledge absorptive capacity and corporate foresight and innovation and strategic decision-making is examined and its effect on organizational performance is analyzed through a structural model.

Using questionnaire and financial analyses, data was collected from the banking industry of Iran including 30 banks (Commercial Government banks, Specialized Government banks, Gharzolhasaneh and Non-Government Banks). Reliability of the measurement model with 93 samples was confirmed through descriptive, inferential statistical analyses and Structural Equation Modeling (SEM) and Importance-Performance Map Analysis (IPMA), using SPSS and SmartPLS software.

The results indicate that there is a significant relationship between knowledge absorptive capacity and corporate foresight. Knowledge absorptive capacity is also indirectly affecting organizationl performance through innovation, corporate foresight and strategic decision-making. Corporate foresight is directly affecting organizational performance and is also indirectly affecting organizational performance with mediation of innovation and strategic decision-making.

Today, the need to use efficiency measurement systems in the modern banking industry has become increasingly apparent. Therefore, the efficiency of banks needs to be forecasted so that future economic growth can be monitored in future decisions. This paper designs a new integrated model based on the Stochastic Data Envelopment Analysis (SDEA) model and the Principal Component Analysis (PCA) method in a dynamic environment to forecast the efficiency of branches in the modern banking industry by considering variable returns to scale for them. In order to deal with the uncertainty in efficiency forecasting, the inputs and outputs of the branches are designed as triangular fuzzy stochastic variables with normal distribution. In this study, Monte Carlo (MC) simulation and meta-heuristic algorithms have been used to solve the proposed model. Finally, in order to evaluate the performance and accuracy of the proposed integrated model, a case study based on modern banking indicators has been presented to forecast the efficiency of the future financial period of the branches and the results have been analyzed.

Evaluating the efficiency of banks is crucial to orient their future decisions. In this regard, this paper proposes a new model based on dynamic stochastic data envelopment analysis in a fuzzy environment by considering the modern banking indicators to predict the efficiency of banks, which belongs to the category of NP-hard problems. To deal with the uncertainty in efficiency forecasting, the mean chance theory was used to express the constraints of the model and the expected value in its objective function to forecast the expected efficiency of banks. To solve the proposed model, two hybrid algorithms were designed by combining Monte Carlo (MC) simulation technique with Genetic Algorithm (GA) and Imperialist Competitive Algorithm (ICA). In order to improve the performances of MC-GA and MC-ICA parameters, the Response Surface Methodology (RSM) was applied to set their proper values. In addition, a case study in the modern banking industry was presented to evaluate the performance of the proposed model and the effectiveness of the hybrid algorithms. The results showed that the proposed model had high accuracy in predicting efficiency. Finally, to validate the designed hybrid algorithms, their results were compared with each other in terms of accuracy and convergence speed to the solution.

As crimes become more complex and the need to investigate and detect crimes quickly in order to arrest criminals, which reduces crime and increases security in society, it is important to pay attention to criminalization; Therefore, this study was conducted with the aim of identifying strategic factors affecting crime detection. The present research is applied in terms of purpose and descriptive-analytical in terms of data collection and analysis method. The statistical population of this research consists of 12 experts and criminologists. The data collection tool was a researcher-made questionnaire. In this study, first, the final factors were identified using the fuzzy Delphi method, and in the next stage, the matrix of cross-effects was designed to measure the impact of factors on each other and identify strategic factors affecting crime detection and provided to experts. Due to the nature of this study, Excel and Mick Mac software were used to analyze the collected data. The findings of this study showed that the factors affecting crime detection in 33 factors and three groups include human, organizational and technological factors; Among these 33 factors, 17 factors were identified as strategic factors affecting crime detection. The results of this study show that in crime detection, teamwork, analysis of crime information, existence of databases of convicted criminals and its field of activity, having technical and laboratory equipment equipped to extract evidence of crime, etc. should be in order to be as successful as possible. To be considered in this regard.

Laws and upstream documents, including the vision document and development plans, which are full-fledged mirror of the country's future strategic projects, signify the excessive importance of futures study. Hence, this study is intended to provide a wide-ranging picture of futures study in the country hoping that a guide for future studies and researches can be developed to increase the quantity and quality of future studies in the field of futurology. This applied research follows a descriptive-analytical method using citation analysis technique. The statistical population includes 238 scientific-research articles with no time limit through total count method of 4 specialized journals of national futures study journals. Data collection tools included library study, processing and analyzing the data in Excel software as descriptive statistics, and MAXQDA software for content analysis. Content analysis of 1144 keywords derived from 238 articles were classified under 34 thematic groups using MAXQDA software. Findings of research in the areas of research approaches and methodology, sampling method, organizational affiliation, scientific participation and content analysis for identify the top research areas of futures research in the country indicated that innovation and diversity in all aspects of research is a requirement for local futures study.