Digital Transformation and Administration Innovation

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.

Digital marketing is recognized as one of the most critical competitive tools in the realm of commerce. The aim of this study was to investigate the effect of digital marketing on the performance of chain stores, with a particular emphasis on the mediating role of marketing capabilities. This research was conducted using a quantitative and applied approach, examining the impact of digital marketing on the performance of chain stores while considering the mediating effect of marketing capabilities. Data were collected through a closed-ended questionnaire using a Likert scale. The validity of the instrument was confirmed by expert opinion, and its reliability was verified using Cronbach’s alpha test. The statistical population consisted of marketing experts in chain stores located in Tehran, with a sample size determined at 150 participants. Data were analyzed using descriptive statistics, Pearson correlation, hierarchical regression, and the Sobel test via SPSS version 26. The findings revealed that among the dimensions of digital marketing, social media had the highest level of application (mean = 4.2), while search engine optimization had the lowest (mean = 3.8). In the domain of marketing capabilities, the innovation dimension was most prominent (mean = 4.2). Regarding store performance, sales growth reported the highest mean (4.1), and customer satisfaction the lowest (3.8). Hierarchical regression analysis showed that digital marketing had a significant and direct impact on store performance (β = 0.52), which decreased to 0.28 after the inclusion of the mediating variable. Simultaneously, the impact of marketing capabilities on performance was also significant and strong (β = 0.45). The mediation test confirmed the significant role of marketing capabilities in transmitting the effect of digital marketing on store performance (Z = 6.70, p < 0.001). The results of this study clearly demonstrate that digital marketing, not merely as a technological tool but as a strategic approach, can play an influential role in enhancing the performance of chain stores.

The present study was conducted with the aim of examining service-oriented business models based on artificial intelligence (AI) using a foresight approach. This research is qualitative, exploratory in nature, and grounded in grounded theory methodology, conducted according to the Strauss and Corbin approach (1998). Data were collected through semi-structured interviews with 15 experts from industry, academia, and technology institutions and were analyzed using open, axial, and selective coding. As a result, 22 conceptual categories were identified across six main dimensions: causal conditions, contextual conditions, intervening factors, core phenomenon, strategies, and consequences. The core category was identified as “Designing a Business Model for AI-Based Service-Oriented Enterprises Using a Foresight Approach.” According to the findings, factors such as weak technological infrastructure, cultural resistance, insufficient specialized training in the AI domain, and a lack of supportive policies were among the key barriers to the implementation of this model. On the other hand, strategies such as the intelligent automation of processes, formulation of modern standards, and the development of employees’ digital skills were introduced as key enablers for the realization of the model. The consequences of implementing this model include enhanced productivity, improved product quality, and the advancement of service-oriented businesses. By presenting a localized and data-driven model, this study can serve as a strategic framework for guiding industrial managers, policymakers, and educational centers in the path toward digital transformation and the development of AI-based service-oriented businesses.

Business intelligence is recognized as a powerful and essential tool across various industries, with the retail industry being particularly well-suited for its application due to the influx of vast volumes of data. In this context, business intelligence in the retail sector is capable of transforming complex and diverse data into understandable and actionable information in a precise and intelligent manner. Therefore, the primary aim of the present study is to design a customer relationship management (CRM) model in the chain retail industry based on business intelligence, using a grounded theory approach. This research, based on the type of data, is qualitative in nature and is categorized as fundamental and exploratory research due to its goal of designing a CRM model in the chain retail industry grounded in business intelligence. Participants in this study included managers and experts involved in the field of customer relationship management in retail stores. The data collection tool was a semi-structured interview, and the method of data collection was field-based. The study employed theoretical sampling, and the sample size reached 22 participants based on theoretical saturation. The qualitative data were analyzed using the grounded theory methodology. According to the results obtained from coding, the following were identified as causal conditions: a culture of business intelligence acceptance, strategic planning based on business intelligence application, understanding the business ecosystem, comprehension of digital transformation, and infrastructural platforms. The central phenomena included customer identification, customer acquisition, recognition of customer needs, reorganization of business processes, customer engagement, and customer dependency. The strategies consisted of inventory management and control, application of business intelligence tools, customer knowledge management, value network management, and analytical, collaborative, and operational CRM based on business intelligence. The intervening conditions were identified as the development of technical infrastructure, qualitative enhancement of software and hardware in database architecture, development of modern technical infrastructures, and localization of information systems. Contextual conditions included cultural factors, social factors, and senior management support. Finally, the identified outcomes of the model were financial performance, improved customer experience, process agility, and the creation of organizational value. Based on the results of the model design, it is recommended that to strengthen business intelligence-based customer relationship management, special attention should be given to the causal factors of the model.