Digital Transformation and Administration Innovation

Timely identification and prediction of negative stock returns represent a critical challenge in financial analysis and risk management, significantly influencing the effectiveness of investment decision-making. This study evaluates the traditional multivariate regression approach alongside the performance of advanced artificial intelligence (AI) optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO), in modeling the probability of negative stock returns. A comprehensive financial dataset was compiled from companies listed on the Tehran Stock Exchange. After conducting preprocessing and feature selection procedures, the models were evaluated based on performance indicators such as accuracy, recall, F1-score, and generalizability. Focusing on Iran's capital market, the research analyzed data from 101 publicly listed companies across two time periods (2010–2015 and 2023–2024). The objective was to assess the accuracy, stability, and generalizability of AI-based models in comparison to the classical regression model. The findings indicate that AI algorithms demonstrate superior performance over multivariate regression due to their ability to model complex, nonlinear relationships between financial variables. These algorithms showed higher predictive accuracy in detecting negative returns. Moreover, their capacity to manage large datasets and reduce statistical noise contributed to enhanced model stability when dealing with irregular and outlier data. These results suggest that employing AI-based optimization methods can serve as an effective tool for market risk analysis and improving decision-making processes under conditions of uncertainty. The present study offers a novel perspective on integrating traditional and intelligent techniques to enhance predictive accuracy in financial markets and may serve as a practical reference for financial analysts and policymakers.

Given the importance of personal branding as a key managerial competency, this study aims to present a hierarchical fuzzy mathematical model for the personal branding of managers within the Agricultural Jihad Organization of Gilan Province. This research is categorized as developmental–applied in terms of its purpose and employs a mixed-methods approach in terms of data nature. The qualitative phase involved a statistical population consisting of professional and academic experts, while the quantitative phase included all heads, managers, and experts with over 10 years of experience at the Agricultural Jihad Organization of Gilan Province. In the qualitative phase, data obtained through literature review and expert interviews were analyzed using thematic analysis. As a result, the dimensions, components, and indicators of managerial personal branding were identified and classified into 5 dimensions, 14 components, and 45 indicators. Subsequently, based on the qualitative model, a quantitative questionnaire was developed. Quantitative data were collected from a sample of 121 employees at the Agricultural Jihad Organization of Gilan Province. These data were then analyzed, and the quantitative model was developed using a hierarchical fuzzy inference system. The most significant outcome of this study is the construction of a hierarchical model for managerial personal branding. This model can be used to predict and evaluate the extent to which managers possess a personal brand within the organization.

The present study aims to design a digital marketing model with an emphasis on artificial intelligence in the insurance industry. This research falls within the category of mixed-methods studies (qualitative and quantitative). The qualitative strategy employed is the grounded theory method, and the quantitative strategy is survey-based. The qualitative population includes 20 experts and managers from the insurance industry, while the quantitative section encompasses all managers and employees in the insurance sector. In the quantitative part, a non-random convenience sampling method was used, and the Cochran formula was applied to determine the sample size, resulting in the collection and analysis of 384 completed questionnaires. To assess the validity of the questionnaire, confirmatory factor analysis (CFA) was employed, and structural equation modeling (SEM) was used to test the research questions. In the qualitative phase, the data were analyzed using MAXQDA software and categorized into causal conditions, core phenomena, intervening conditions, contextual conditions, strategies, and outcomes. In the quantitative phase, using SmartPLS 3 software, two models—standard and significance models—were constructed. The path coefficient between causal conditions and the core phenomenon was 0.598 with a significance value of 7.644. The path coefficient between the core phenomenon and strategic factors was 0.635 with a significance value of 7.640. Additionally, the path coefficient between contextual conditions and strategic factors was 0.651 with a significance value of 8.021, and the coefficient between intervening conditions and strategic factors was 0.721 with a significance value of 9.458. Finally, the path coefficient between strategic factors and outcomes was 0.624 with a significance value of 8.450. These findings indicate that the components of the proposed executive model significantly and positively influence one another, and the overall model demonstrates a desirable level of fit.

In the complex and dynamic world of today’s organizations, institutionalizing spirituality in the workplace is considered a key factor in improving organizational performance, enhancing employee commitment, and promoting an ethical climate. This is especially important in educational organizations, which serve as the foundation for the development of societal values. In such settings, fostering and reinforcing organizational spirituality in interaction with the ethical climate can create the groundwork for improving both individual and organizational functions. The present study aimed to design a model for institutionalizing organizational spirituality with an emphasis on the dimensions of ethical climate in the Khorasan Razavi Department of Education, in order to identify and analyze the reciprocal effects of the components of these two variables. The study is applied in nature and employs a mixed-methods approach (qualitative–quantitative). In the qualitative phase, using the grounded theory method and conducting semi-structured interviews with 15 educational and administrative experts, the key components of spirituality and ethical climate were extracted. In the quantitative phase, the conceptual model derived from the qualitative analysis was tested using structural equation modeling (SEM) and confirmatory factor analysis (CFA). The statistical population consisted of employees and managers of the Khorasan Razavi Department of Education. In the quantitative phase, stratified random sampling was employed, resulting in the collection and analysis of 320 completed questionnaires. The results of structural equation modeling showed that the dimensions of organizational spirituality—namely, meaning and purpose in work (β = 0.78), sense of belonging (β = 0.71), spiritual connection (β = 0.74), and ethical values (β = 0.69)—had a significant and positive impact on the organizational ethical climate (p < 0.001). Furthermore, the dimensions of ethical climate—namely, justice (β = 0.81), accountability (β = 0.76), empathy (β = 0.73), and organizational transparency (β = 0.79)—played an effective mediating role in the relationship between organizational spirituality and improvement in organizational performance. The model’s coefficient of determination (R²) indicated that 64% of the variance in the organizational ethical climate could be explained by the components of organizational spirituality. Based on the findings, strengthening spirituality in educational environments leads to improved employees’ mental health, increased productivity, enhanced accountability, and reduced organizational conflict. Education administrators can benefit from this model in macro-level policymaking, designing human resource development programs, and fostering an organizational culture grounded in spirituality and ethics. This research takes a step toward a deeper understanding of the interaction between spirituality and organizational ethics in educational settings and can serve as a foundation for future research in this area.

This study aims to examine how fan and media pressure influence the selection and dismissal of head coaches in professional football, comparing dynamics across Iranian and European leagues. This article adopts a scientific narrative review approach using a descriptive analysis method. Relevant literature from 2018 to 2025 was collected from peer-reviewed journals, sports management publications, media case reports, and official club communications. The study focuses on five thematic areas: theoretical frameworks of decision-making, mechanisms of fan influence, media framing and its consequences, historical case patterns in coaching changes, and a comparative analysis of Iranian and European contexts. Both qualitative and quantitative sources were synthesized to reveal underlying trends and contextual differences. The review highlights that fan pressure operates through channels such as stadium protests, social media campaigns, and supporter associations, often compelling clubs to act despite stable technical performance. Media pressure, driven by framing tactics and pundit narratives, shapes public and executive perceptions of coaching effectiveness. In both Iranian and European contexts, coaches increasingly face shortened tenures due to these external forces. However, institutional autonomy, media freedom, and the professionalism of club governance significantly mediate these pressures. In Europe, clubs manage external narratives through strategic frameworks, while Iranian clubs, embedded in politicized and less autonomous structures, respond more reactively to public and media sentiment. Fan and media pressure have become integral to football governance, transforming coaching decisions into public performances subject to emotional and symbolic scrutiny. Understanding these dynamics is crucial for clubs aiming to balance stakeholder expectations with long-term strategic planning. Comparative insights underline the need for culturally and institutionally sensitive approaches to managing external influence on coaching stability.

The aim of this study is to model and evaluate customer knowledge management (CKM) processes in industrial companies affiliated with the Mostazafan Foundation. This research is applied in terms of purpose and descriptive-analytical in nature. It adopts a mixed-methods approach and has been conducted in both qualitative and quantitative phases. The statistical population in the qualitative section included academic experts and managers of industrial companies under the Mostazafan Foundation. Using the snowball sampling method and the principle of theoretical saturation, 12 individuals were selected as the sample. The data collection tool in the qualitative phase was a semi-structured interview, grounded in a previously extracted theoretical framework. Data analysis in this section was performed using grounded theory. The results of the qualitative phase were presented in the form of four main categories and nineteen subcategories. The quantitative part of the study was conducted using a researcher-made questionnaire derived from the qualitative model and distributed within the statistical population. After confirming the validity and reliability of the questionnaire, 213 participants were selected through random sampling to complete the questionnaires. The findings of the qualitative phase indicated that the dimensions, drivers, strategies, and consequences of the customer knowledge management model in the studied industrial companies include the following elements: assessment of the current state of organizational knowledge; collection, documentation, and transfer of customer knowledge; effective communication with customers and a comprehensive understanding of their needs and preferences; focus on the process of knowledge creation around the customer; psychological profiling and behavioral analysis of customers; customer feedback strategies (through surveys, comments, reviews, and interviews); emphasis on the company’s knowledge-based products; reviewing the history of current customers (previous purchasing behaviors); implementing creative ideas for products and services; training in knowledge transfer and management methods; strengthening technological infrastructure; co-creation of value with customers; benchmarking sales of new products against competitors’ products; measuring goal attainment levels; enhancing efficiency in customer service and customer orientation; digital self-service adapted to customer needs (in the area of customer support); intelligent routing of customer requests to relevant experts; maximizing value creation from knowledge; strategic-level knowledge management; and improving quality and speed in decision-making and customer service. The causal pathways and relationships between external and internal constructs of the structural model were validated using confirmatory factor analysis.

The main objective of this research is to model the technology transfer process in Iran's petro-refining industry using the system dynamics method in order to improve this process. This analysis assists decision-makers in identifying critical success factors and designing optimization strategies for the technology transfer process. Following the system dynamics approach, this study investigates the dynamics of variables affecting the development and improvement of the technology transfer process in Iranian petro-refineries through a review of relevant studies and interviews with industry experts. Eight subsystems were identified in this study: organizational and environmental infrastructures, technology monitoring and selection, technology acquisition, technology learning and localization, knowledge management, innovation system, technology development and improvement, and technology dissemination. The causal loop diagrams associated with these subsystems were developed using Vensim software. Ultimately, the analysis of the causal loop diagrams indicates that the primary enabler for optimal technology transfer in Iranian petro-refineries is the existence of an organizational body dedicated to the leadership, coordination, and control of the technology transfer process. The absence of such an organization will hinder the optimal completion of the technology transfer process.

This study aims to explore how social media platforms contribute to collaborative innovation, the development of human and social capital, and the promotion of urban sustainability practices in Tehran. Employing a qualitative research design based on Grounded Theory, this study collected data through in-depth, semi-structured interviews with 12 purposefully selected participants actively engaged in social media-based knowledge sharing, environmental activism, and innovation. Participants were diverse in terms of age, gender, education, and profession. Data collection continued until theoretical saturation was achieved. Thematic analysis was conducted using open, axial, and selective coding procedures. Credibility of the findings was ensured through member checking and triangulation of viewpoints. Analysis revealed four main categories through which social media enhances urban innovation and sustainability: (1) enhancing environmental literacy through awareness campaigns; (2) enabling collaborative innovation via citizen problem-solving; (3) fostering behavioral change through peer-generated content; and (4) facilitating social mobilization through hashtag activism and online coordination. Participants emphasized the role of social platforms in generating ecological awareness, sharing grassroots solutions, and fostering digital communities that promote sustainable behaviors. The findings highlight the interplay between human capital and social capital as central to the innovation potential of social media in Tehran’s urban context. Social media functions as a participatory infrastructure for civic innovation and sustainability in Tehran, enabling decentralized learning, peer-to-peer influence, and digital coordination. These platforms empower citizens to share knowledge, co-create urban solutions, and engage in environmental advocacy, particularly in contexts where formal institutional pathways are limited. The integration of digital tools into urban governance and community development strategies is essential for fostering inclusive, sustainable urban futures.