جستجوی مقالات مرتبط با کلیدواژه "r" در نشریات گروه "مدیریت"

The purpose of this research is to present a paradigmatic model of financial performance in the banking industry with a focus on supporting small and medium-sized enterprises (SMEs). The present study is applied in terms of its objective and qualitative in terms of its method. The target population consisted of experts familiar with the research topic, including university professors in the fields of banking and entrepreneurship, as well as senior managers from Bank Mellat. The sampling was done theoretically, and interviews were conducted with 12 experts until saturation was achieved. The research approach was grounded theory, which involved open, axial, and selective coding through interviews with the experts. Data were collected through expert interviews. To assess the validity of the research, the methods of review during coding and examination by another informed individual were used to ensure the accuracy of the coding. In this study, the test-retest reliability method was employed to determine the reliability coefficient. Based on the research findings, it was observed that the financial performance of the banking industry in supporting small and medium-sized enterprises comprised 142 open codes, 18 categorical codes, and 6 final axial codes, including six main components: causal conditions (financing), central phenomenon (financial support), intervening condition (financial policy), contextual condition (infrastructure), strategies (financial strategies), and outcomes (sustainable growth). The presented paradigmatic model indicates that effective banking support for SMEs can contribute to the growth and sustainability of these businesses.

The purpose of this research is to investigate the variables (self-confidence, communication, anxiety, social benefits, social good, attitude towards education and people's preparation) on the behavioral intention of tourism students towards the use of artificial intelligence.

The current research is classified as a descriptive survey research in terms of its practical purpose and in terms of its research method, and the statistical population is tourism students across the country. Statistical analyzes were also performed using spss and Amos software, and the regression method was also used in the hypothesis path analysis test, and it also displays the mean, standard deviation, skewness, and kurtosis.

The results of the research showed that all the factors and variables of the research have a positive and significant effect on the behavioral intention, except the perceived usefulness, which hypothesis was rejected, and the result showed us that the variables have an important and significant effect on the behavioral intention of the people. And by controlling these variables in the education system of the country, especially tourism, a suitable platform for optimal education can be provided.

The ways in which consumers interact with businesses have changed significantly due to the rapid and numerous developments that have occurred in recent years. In addition to traditional sales centers, companies have begun to offer other interactive channels such as web and smartphone applications, social networks, digital stores and contact centers to their customers. In this context, a phenomenon called "Omni channel" has emerged, where customers can use not only one of the existing interaction channels, but all channels simultaneously. For this reason and in this regard, the present study was conducted with the aim of presenting a model for integrating Omni channels in the banking industry.

The approach of the article is qualitative and in terms of its purpose is applied-exploratory. In this way, data were collected through related texts, in-depth interviews and semi-structured interviews with 15 experts, and a thematic analysis strategy including coding was also used to achieve the model extracted from the article. The data were also analyzed using coding and Max Quad software.

Finally, the quality model of integration of collaborative channels was designed with three components (levels): 1- Dimensions of model integration quality, 2- Drivers of the model (facilitators), 3- Consequences of the model and in 12 dimensions and 50 indicators.

By combining interactive elements and immersive narratives, interactive storytelling offers a powerful tool for engaging target audiences and creating an unforgettable experience that allows brands to break free from the limitations of traditional marketing and connect with their audiences on a deeper level. This approach transforms passive observers into active participants, creating a more memorable and impactful experience. This research aimed to identify and analyze the antecedents and consequences of interactive storytelling in digital marketing. This research is exploratory in terms of its applied purpose and in terms of its data collection method, in which digital business managers and marketing and e-commerce professors were selected as samples. The present study is mixed research with an exploratory approach, in which in the qualitative part, qualitative data collected using the opinions of 19 experts were analyzed using MaxQDA software and content analysis and coding methods. Then, in the quantitative part, the data was provided to the same sample in the form of a paired comparison questionnaire and analyzed using the fuzzy cognitive map method. The results showed that among the antecedents of interactive storytelling in digital marketing, immersion has the highest capacity for impact and persuasive story has the highest capacity for impact. Also, among the consequences of interactive storytelling in digital marketing, awareness of customer interests has the highest capacity for impact and personalization has the highest capacity for impact.

In today's economy, small and medium-sized enterprises (SMEs), especially those offering advanced technology products and services, strive to seize opportunities in the international market. As their primary clientele consists are businesses and grapple with domestic demand challenges, identifying effective B2B marketing strategies from knowledge-based companies can serve as a blueprint for other firms, helping to mitigate their risks. The aim of this study is to develop a model for B2B marketing strategies suitable for SMEs operating in various industries and locations by analyzing the successful strategies employed by knowledge-based companies in the international market, without being constrained to a specific industry or region. To gather research data, semi-structured exploratory interviews were conducted with managers from 27 knowledge-based companies, utilizing a storytelling approach. The collected data were subsequently analyzed using thematic analysis, and the Importance-Performance Analysis (IPA) method was employed to compare the current and desired states of B2B marketing strategies within the knowledge-based business ecosystem. Ultimately, 25 strategies were identified and categorized into five groups based on their objectives and processes: Insight Generation (Market Research), Awareness Building (Digital Marketing and Brand Awareness), Skill Enhancement (Negotiation and Bargaining), Synergy (Collaboration and Networking), and Trust Building (Value Creation and Competitive Advantage). The findings also reveal that strategies such as “offering customized proposals,” “providing rapid and integrated after-sales services,” and “utilizing AI tools in market research” are highly important but currently underperforming among small and medium-sized knowledge-based companies. It is recommended that businesses focus on establishing international collaboration networks with other companies and research institutions. For instance, knowledge-based companies in the biotechnology sector can collaborate with universities and research centers in target countries on green and sustainable technology projects to showcase and present their capabilities and capacities. Furthermore, the Vice Presidency for Science and Technology and the Ministry of Industry, Mine, and Trade can play a pivotal role in promoting these companies’ products and services in global markets by organizing joint international exhibitions where Iranian knowledge-based companies can demonstrate their capabilities.

The purpose of this study is to cluster the Iranian online shopping consumer market using artificial neural network, so that based on it, customers' needs can be better identified, the characteristics of each cluster can be determined more accurately, and the best clustering method can be chosen. And finally, the development of appropriate strategies for management, communication and better service to customers was achieved. Based on the purpose, the present research is descriptive and of the estimation and evaluation type, and in terms of practical purpose and in terms of time period, the situation of customers has been studied during the years 2021 to 2022. The statistical population included 52,403 online stores, and the present study selected 349 stores based on simple sampling. The method of analysis and classification of data is done by RFM, K-Means and self-organizing fuzzy-neural network. The technique used was the sum of squared error criteria and the Davies-Bouldin index. The findings showed: food items (they had the least delay in purchasing due to frequent needs); cosmetics (the majority of purchases were made by women); Luxury appliances (have the highest monetary value of purchase); industrial supplies and their accessories (the most purchases were made by men) and finally, sanitary supplies, detergents and clothes (have the most frequency of purchases). The results of the research have shown that the use of self-organizing neural networks along with the RFM method is the most suitable method for clustering and separating and valuing customers. Also, Kmeans+ANFIS also achieved good values, but the WRFM+ANFIS method has been more successful in this index.

Because of the non-linear fluctuations of the stock price, it is challenging to predict. Therefore, it is important to identify the characteristics that can be used to predict market behavior. Both traditional and modern methods are very important for these features. Among these features, we can mention the feelings and emotions of consumers. In this research, the effect of consumer sentiment factor in predicting market fluctuations has been investigated. For this purpose, the S&P500 index has been considered for forecasting first without considering the characteristics of consumer sentiments using BiLSTM deep neural network and then by combining the UMCSENT consumer sentiment factor. The experiments and results of this research show that the use of consumers' feelings and emotions increases the accuracy of forecasting the S&P500 index.

Subject: 

This research examines how the intelligence of certain entrepreneurs allows them to effectively navigate crisis situations and even seize entrepreneurial opportunities in such markets. The Covid-19 crisis, wars in the West Asian region, terrorist groups and international sanctions have created complex conditions for Iranian entrepreneurs. crisis can be a suitable field for studying entrepreneurial learning. Here we want to study the entrepreneurial learning process in crisis conditions and describe and explain this process as much as possible.

This study is a qualitative research conducted using a multiple case study method of eleven founders of knowledge-based businesses in Iran who had gone through various crises, but were successful not only in the Iranian market but also expanded their services in international markets.

The findings of this research indicate the importance of learning from the experience of past crises to manage current and future crises. Also, entrepreneurs go to trial and error and develop new products in crisis situations where old and reliable solutions don't work and communicate with customers to evaluate their ideas.Studying and learning from other people's experiences is also a topic that has been very little discussed in the literature. The entrepreneurial learning literature seems to direct entrepreneurs to personal experience to learn any subject, while the study of entrepreneurs rejects this.Finally, regarding the consequences of learning in crisis, this study shows that learning from the internal network can lead to exploitative and explorative learning at the same time, but external networks can only lead to explorative learning.This research expands previous results regarding the outcomes of entrepreneurial learning and presents a new perspective on the learning process in crisis situations.The main streams of literature in the field of entrepreneurial learning have paid very little attention to the learning process, especially in certain situations such as crisis situations. Understanding this issue can help us how businesses can overcome crisis conditions. On the other hand, crisis is a suitable field for the entrepreneurial learning process to be investigated more clearly.

The purpose of this research is to design an interpretive structural model for internal Intelligent marketing, focusing on an intra-organizational approach in businesses that implement smart technologies in their operational processes.

The research employs a mixed-method approach with a qualitative, exploratory design. It is categorized as applied research due to its practical relevance for businesses. Thematic analysis was used to analyze the data, while Andrewsage's (1977) Interpretive Structural Modeling (ISM) method was utilized to identify the relationships between variables, classify indicators based on the interpretive paradigm, and develop the model. The research sample included executive managers from furniture manufacturing businesses in the Kurdistan region of Iraq, all of whom use internet-based technologies to digitize their organizational processes. A total of 21 managers were interviewed, selected through snowball sampling until theoretical saturation was reached.

The findings of the study reveal that factors related to internal intelligent marketing were categorized into six hierarchical levels. At the first level is internal intelligent marketing itself, followed by smart marketing campaigns at the second level. The third level includes digital talent management and digital skills development platforms. The fourth level consists of an online performance evaluation platform, predictive employee analytics, and an online training platform. The fifth level includes online monitoring systems, digital knowledge bases, digital learning networks, and online information systems. Finally, the sixth level encompasses digital technology infrastructure, online social networks, government regulations, and the organization's digital culture.

The results indicate that intelligent marketing campaigns, digital learning networks, digital knowledge bases, and online information systems are critical components in the target area. In the affected area, digital culture, online social networks, digital technology infrastructure, and government laws and regulations play significant roles. The impact zone includes the online performance evaluation platform, digital skills development platform, digital talent management platform, and online monitoring systems. Additionally, the analysis shows that the digital culture factor had the highest influence score (rij = 2982), while the intelligent marketing campaign platform had the greatest impact score (rji = 1677). These findings provide valuable insights for businesses looking to enhance their internal intelligent marketing.

Smart statesmanship refers to the integration of advanced technologies across three key domains of national administration: governance, public administration, and executive operations. This paper presents a conceptual framework for Smart Statesmanship, examining the digital transformation trends in societal management and analyzing the impact of technologies such as artificial intelligence, cloud computing, machine learning, and the Internet of Things on statesmanship processes. Smart governance, with a focus on policymaking, regulation, and the formulation of national standards based on transparency, citizen participation, and data-driven decision-making, plays a pivotal role in optimizing government processes and enhancing accountability. Smart public administration, through automation and the use of big data in planning, organizing, directing, and controlling the public sector, increases the efficiency of governmental systems and strengthens interorganizational collaboration. Smart executive operations enhance productivity and sustainability by optimizing urban infrastructure, intelligent transportation systems, energy management, and environmental monitoring systems. The paper also addresses the challenges and risks associated with Smart Statesmanship, such as cybersecurity threats, the digital divide, institutional resistance, and ethical considerations, and proposes strategies for successful implementation. Finally, it emphasizes the necessity of integrating these three domains into a comprehensive model to achieve Smart Statesmanship.

Tendering in economic activities is aimed at creating equal opportunities for economic actors and discovering the lowest price for public or executive organizations. A significant portion of commercial and industrial activities in public or public entities involves large-scale transactions, necessitating either public or restricted tenders. Annually, numerous commercial transactions are conducted through tenders, and even minor deviations from the law in this domain can result in major economic corruption and considerable financial losses. The purpose of this paper is to design a system based on fuzzy expert system methodology to evaluate the integrity of tender processes. The research adopts an exploratory approach and is conducted using expert systems methodology. The proposed system includes a knowledge base containing rules that infer the level of compliance or deviation from the law using if-then logic. These rules are derived from higher-level legal regulations and expert opinions, particularly those in supervisory organizations, and are then transformed into if-then statements. MATLAB software is employed for the design of the fuzzy expert system, enabling the collection of rules, rule coding, and fuzzy inference. The results include 30 fuzzy rules for assessing the integrity of tenders. The designed system can be utilized by regulatory bodies, supervisory entities, and any organization involved in tenders to ensure compliance with regulations and the integrity of tender processes.

Technological advancements in the modern era have revealed the inefficiencies of traditional governance models and highlighted the need for emerging technologies to enhance governance structures. Contemporary societies are seeking greater efficiency, transparency, and public trust, compelling governments to adopt innovative technological tools. Blockchain technology, with its inherent characteristics of immutability, transparency, and data security, has significant potential to contribute to urban governance. In recent years, blockchain has been utilized worldwide for managing citizen data. This study aims to identify and prioritize the drivers and barriers to blockchain adoption for smart governance in Tehran. Following an initial list derived from a review of relevant literature and its validation by experts, the Importance-Performance Analysis (IPA) framework was employed to prioritize these factors based on expert opinions, focusing on the most critical drivers and barriers. Additionally, a focus group of urban management experts was convened to finalize the study findings and propose actionable recommendations. The results indicate that the primary barriers include political, technical, economic, cultural, and legal limitations. Key challenges involve the absence of clear regulations, insufficient technical infrastructure, and high initial costs. From a cultural perspective, resistance to adopting new technologies and legal ambiguities are notable obstacles. Conversely, the drivers of blockchain adoption include enhanced transparency, cost reduction, strengthened public trust, reduced corruption, and improved inter-organizational communication. The study’s recommendations include drafting clear regulations, investing in technological infrastructure, providing financial incentives, and organizing training programs. These measures can help address the barriers and leverage the drivers to achieve smart governance in Tehran.

 This study was conducted with the aim of determining the difference in physical performance related to health and movement of students of different levels of military education. To conduct this study, 99 students of Imam Ali University were selected in three groups first year (35 people), second year (33 people) and third year (31 people) based on availability sampling. In this study, trunk endurance was evaluated with the McGill test series. Static and dynamic balance was also evaluated with stork and Y balance tests, respectively. To evaluate the function of the lower limb, single leg hop test, triple crossover hop for distance and timed single leg hop test were used. Upper limb function was evaluated with upper limb Y test. ANOVA statistical test and Bonferroni's post hoc test were used to compare the difference between groups. The results of one-way analysis of variance showed that there is a difference between the three groups of the first year, the second year and the third year in variables related to endurance such as flexion 60 degrees (p=0.005), Sorensen (P=0.03), plank (P=0.02), right plank (p=0.01), total endurance score (p=0.001) , internal direction (p=0.001) as well as the total score of upper limb function (p=0.001), single leg hop test (p=0.001) and triple crossover hop test (p=0.001). Based on the results of this study, it seems that trainers and specialists active in the field of education of Imam Ali Officer University should use exercises related to balance and upper limb function during training programs.

Psychological contracts are formed in people's minds and their satisfaction or lack of satisfaction crystallizes in their behavior and attitude and leads to behavior and actions that create value for the organization, so strengthening these contracts becomes more important in the organization. In this article, the factors that strengthen psychological contracts in military organizations are identified. The research method of the present study is a qualitative type of thematic analysis based on a homogeneous purposeful sampling. 21 commanders and managers in military organizations (Artesh, Sepah, Faraja and Ministry of Defense) were selected as key informants and during the in-depth semi-structured interview, they fully shared their opinions and experiences regarding the consequences of psychological contracts in military organizations. they said. In the data analysis, the theme analysis method was used, and to determine the validity of the findings, the criteria of credibility, reliability and compliance with objectivity and auditing by the referee were used. The findings of the research were categorized in the form of 2 overarching themes, which is the result of information extraction in 1060 basic themes and 20 organizing themes. In sum, the findings indicate that the commanders with being role models in different dimensions and paying attention to the spiritual, intellectual and psychological needs of the troops in addition to providing their well-being and growth and promoting their careers on the one hand and the troops by strengthening their faith and belief in God and considering God's pleasure in doing Actions cause psychological contracts.

In today's era,in order to accurately understand the media and stay away from the harms of the digital world and the onslaught of media messages,having media literacy is very necessary and important for the officials of every country at the society level.One of the harms that may be caused by the media,virtual space and social networks is affecting people's cognition and way of thinking. The current research is applied in terms of purpose and descriptive method with a mixed approach. The statistical population of this research in the qualitative stage is library documents and interviews with11experts in cognitive warfare and media literacy.In the quantitative stage,a targeted sample size of 140 experts and professors of media literacy and cognitive warfare of Aja officer universities and other parts of the organization was estimated,and the sample size was determined to be 103 people to answer the questionnaire using Morgan's table.MAXQDA software was used to categorize and analyze the data obtained from interviews with experts and documents and documents,and SPSS and Excel software were used to analyze and analyze quantitative data, and one-sample t-test was used to measure the research hypothesis. The result of this research shows that by considering the three dimensions of knowledge structures,media skills and personal decision-making center under13components and 63 executive strategies which are ranked respectively,it is possible to improve students' media literacy in the officer universities of the Islamic Republic of Iran Army.Upgraded in such a way that they can perform properly in the face of cognitive warfare

Identifying, predicting and evaluating the threats of new technologies with indicators such as correct and accurate recognition of the threat, evaluating the strength and capacity of the threat is important and vital to protect the interests of our beloved country in the future battles.

The current research has been carried out with the aim of designing the pattern of threats of modern technologies of the Army of the Islamic Republic of Iran.

This research is of applied-developmental type, which has a mixed approach with descriptive-analytical method. The data collection method was library and field, in-depth interviews were conducted with 11 experts and a sample size of 85 people. In the qualitative part, content analysis was done by refining, summarizing and displaying data, and in the quantitative part, descriptive and inferential statistics and spss software were used.

In order to achieve the design of the desired model, the items related to the questionnaire created by the statistician were completed and presented to the expert community and the sample size. the result of which three components (artificial intelligence, robots and future/cyber soldiers) and 10 indicators in the field of threats of modern technologies were calculated and the data analysis in this field was also completed.

Originality: 

The results indicate that the components of artificial intelligence, robots and future/cyber soldiers with a combination of 10 indicators in the field of threats of new technologies provided the components of the mentioned model, which were further validated by the expert community.

The views and thoughts of the leaders and elites of a country can draw a road map for the realization of national goals and interests. Meanwhile, the school of Lieutenant General Martyr Ali Sayad Shirazi is the necessity of our country today due to the extensive attacks of the enemy, and it can be used as a practical model for the administrative and executive departments in the country. In this regard, this research has examined and analyzed the indicators of the educational and moral school of Martyr Lieutenant General Ali Sayad Shirazi in the Islamic Republic of Iran. The current research is applied research in terms of benefit and purpose, The research method of this research is "foundation data" based on which and in line with the goals of the research in a purposeful and systematic manner in such a way that the extracts of the educational and moral school of Lieutenant General Martyr Ali Sayad Shirazi can be extracted, conceptualized, categorized and then modeled, examined and The analysis is done. In this regard, in the first stage, 216 propositions were extracted in the form of 193 concepts. In the second stage, 31 subcategories were categorized and counted. In the third stage, based on the model of Strauss-Corbin's theory and its 6 main categories, the systematic model of the educational-ethical school of Martyr Sayad Shirazi was presented to develop the country's political, cultural, security and defense doctrine and strategies in order to face the complex and combined enemy war. Is.

The interplay between politics and public policy significantly influences governance and societal progress, particularly in Iran. Politics, encompassing power dynamics and ideologies, shapes public policymaking, which serves as a tool to address societal issues. Understanding this relationship is vital for advancing policymaking knowledge. This paper explores the conceptual distinction between politics, rooted in political science, and public policy, studied in policy analysis. It critiques ambiguous terms like "public policy politics" and "political policy," suggesting clearer alternatives such as "public policymaking politics" to enhance understanding. The study identifies key challenges in this interaction, including short-term political interests, inequality in policy implementation, and populism, all of which can distort justice and undermine public good. Despite these challenges, the paper highlights the potential for positive outcomes through increased transparency, accountability, and collaboration among political actors, fostering a more equitable policymaking process. Ultimately, while politics can negatively impact policy, it also provides an opportunity to create just, evidence-based, and sustainable public policies. By addressing political influences constructively, policymakers can ensure governance prioritizes fairness and long-term societal benefit over political expediency. This analysis underscores the dual nature of politics in shaping public policy—both as a challenge to justice and a potential catalyst for progress.

This study aims to design an integrated competency model for human resources in Iran’s Ministry of Energy, utilizing an architectural approach. In the first phase, to identify the dimensions and components of the integrated competency model, a qualitative method (thematic analysis) was employed. In the subsequent phase, the fuzzy Delphi method was used to reach consensus on the findings from the qualitative analysis, and the fuzzy SWARA technique was applied for prioritizing the dimensions and components. The study involved semi-structured interviews with twelve experts, including specialists from the Ministry of Energy, affiliated companies, and academic faculty, who were purposefully selected. The research findings identified four main constructs that constitute the Ministry's integrated human resource competency model: “Competent Human Resource Managers,” “Competent Systems and Processes,” “Competent Human Resources,” and “Organizational Strategies in Human Resources.” The first construct, “Competent Human Resource Managers,” encompasses “communication skills, team-building skills, and leadership skills.” The second construct, “Competent Systems and Processes,” includes “educational development processes, effective human resource processes, and organizational coordination processes.” The third construct, “Competent Human Resources,” comprises “strategic competencies and operational competencies.” Finally, the fourth construct, “Organizational Strategies in Human Resources,” consists of “paternal and committed strategies.” The paper concludes with recommendations for implementing the designed model within the Ministry of Energy.

This study aims to develop scenario planning as a method for policy laboratories. The institutional structure of science and technology policy in Iran was selected as the case study, with in-depth, semi-structured interviews conducted with 20 experts and informants in Iranian science and technology policy. Schwartz’s eight-step scenario planning method was applied. Based on this, two key uncertainties—1) Structure (open/closed) and 2) Rules of Conduct (collaborative participation vs. contentious dispute)—were identified, leading to four scenarios: 1) Collaborative Policy Network, 2) Government System, 3) Obligation-Relief Approach, and 4) Island Structure. The outcomes of each scenario were evaluated, and the most desirable scenario, the Collaborative Policy Network, was selected. This study demonstrates that scenario planning, a widely used method in foresight studies, can also function as a policy laboratory by assessing the potential consequences of a policy. It is recommended that science and technology policymakers evaluate policy outcomes in a policy laboratory through methods like scenario planning before implementing them broadly and subjecting them to public trial and error.