Digital Transformation and Administration Innovation

The environment in which 21st-century humans live has undergone profound transformations. Today, the emergence of digital technologies has brought about an unprecedented transformation in workplaces, shifting the nature of work from its physical and task-based form to a digital modality. The present study was conducted with the aim of developing a model of digital employee experience in Iranian banks. Organizational success in the digital age depends on how work-related activities are transformed in digital work environments with a focus on improving employee experience. This research employed a mixed-method approach: qualitative content analysis with an inductive approach in the qualitative phase, and factor analysis in the quantitative phase. Based on the principle of theoretical saturation, 14 experts and academics in the fields of marketing science, digitalization, customer relations, and employee experience were interviewed using purposive criterion-based sampling and semi-structured interviews. The findings resulted in six overarching categories forming the model: core digital competencies, digital organizational culture, digital policies, digitalization challenges, experience-oriented employees, and banking management. Moreover, the factor analysis of the dimensions of digital employee experience and its impact on improving banking performance in the quantitative section showed a good model fit.

This study aims to design a public policy model for information technology-based education in the municipalities of Iranian metropolises using a qualitative research approach and grounded theory methodology. Data were collected through in-depth interviews with 16 academic elites and senior managers and were analyzed until theoretical saturation was achieved. The coding process included three stages: open, axial, and selective coding, ultimately leading to the extraction of six main categories and 106 subcategories. The findings revealed that employee participation, a participatory organizational culture, transparency in actions, and the development of cultural-educational programs are among the key factors in formulating effective policies. Furthermore, legal and environmental barriers—such as economic challenges and the absence of feedback mechanisms—exert a significant influence on the policy-making process. The proposed strategies were formulated across three levels: short-term (motivational and behavioral), mid-term (research-based and social), and long-term (cultural and legal). The results emphasize that aligning educational programs with organizational needs and strengthening management information systems plays a fundamental role in enhancing the quality of IT-based educational policymaking. By presenting a localized model, this study offers a practical framework for urban policymakers to optimize educational processes.

The aim of this study is to discover the components and indicators of internal branding in nonprofit organizations in Iraq. This research adopts an interpretivist philosophy, an inductive approach, a qualitative method, and a phenomenological strategy. The qualitative study population includes managers and employees of nonprofit organizations in Iraq engaged in charitable and benevolent activities who have at least 10 years of experience in branding and internal branding within these organizations, and who also possess sufficient awareness and knowledge of the foundations and principles of internal branding. The sampling method in this research is non-random and purposive. Data collection was conducted through semi-structured interviews. According to the qualitative content analysis conducted, internal branding in nonprofit organizations comprises 11 components, 40 categories, and 342 codes. These 11 components include: employees’ internal communication with the brand, brand goal identification, brand commitment influenced by human resources, creation, recognition, understanding, and transfer of brand value by human resources, brand perception by organizational employees, alignment and value congruence of human resources with the brand, employee support for the brand, brand identity formation and transfer of brand objectives to human resources, brand clarification by employees, brand-consistent behaviors, and extra-role brand-consistent behaviors by human resources. The findings emphasize that while general principles of internal branding are applicable in Iraq, the country’s specific conditions necessitate localized strategies. Notably, the shortage of resources frequently observed in many nonprofit organizations in Iraq, combined with the significant role of informal relationships among employees—a prominent feature of Iraq’s collectivist culture—require that conventional branding approaches be adapted to local needs. This study partially addresses this necessity through its findings.

This study aimed to validate a structural model of smart tourism by examining the impact of multiple technological, behavioral, and managerial constructs on the development of smart tourism in Kish Island, Iran. The research employed a quantitative design using a descriptive-correlational strategy and structural equation modeling (SEM) to evaluate the proposed model. A two-stage sampling method was applied: first, cluster sampling was used to randomly select 30 hotels from 51 active establishments in Kish Island; second, simple random sampling was used to select tourists from these hotels. Out of 311 distributed questionnaires, 273 were deemed valid and analyzed. A 45-item smart tourism scale developed by the researchers was used for data collection, with its content validity confirmed by experts (CVI = 0.82). Cronbach’s alpha, composite reliability (CR), average variance extracted (AVE), and discriminant validity tests were conducted to ensure measurement reliability and validity. Data were analyzed using SPSS-24 and SmartPLS-3. All eight independent variables—perceived value, economic development, smart technology, tourist behavior, complementary activities, destination capability, information management, and smartification—had statistically significant effects on smart tourism. Smart technology (β = 0.269, p < 0.001) and economic development (β = 0.199, p < 0.001) showed the strongest influences. Model fit indices, including AVE (>0.50), CR (>0.70), and goodness-of-fit (GOF = 0.725), confirmed the model’s validity and predictive power. Discriminant validity was also established using the Fornell-Larcker criterion. The validated smart tourism model demonstrates that technological infrastructure, managerial readiness, and tourist-centered strategies are essential for developing smart tourism destinations. These findings offer both theoretical insight and practical guidance for enhancing tourism innovation, competitiveness, and sustainability in similar regional contexts.

This study aims to present a comprehensive conceptual framework for integrating artificial intelligence into personalized marketing within the tourism industry during the era of the Fourth Industrial Revolution. It examines the role of this technology in enhancing traveler experiences and improving marketing strategies. Using a qualitative research approach and semi-structured interviews with 11 experts in the fields of marketing, artificial intelligence, and technologies related to the Fourth Industrial Revolution, data were collected and analyzed through thematic analysis. Based on the analysis, a conceptual framework was developed from 219 concepts extracted from the data. The findings of the study indicate that artificial intelligence can play a pivotal role in data management, enabling the analysis of big data and identification of traveler behavior patterns, predicting preferences and needs through machine learning algorithms, and designing precise marketing strategies to deliver personalized travel services and experiences. These capabilities significantly enhance the effectiveness of marketing strategies in the tourism industry. The proposed conceptual framework not only contributes new insights to the scientific literature on marketing and artificial intelligence but also serves as a practical guide for tourism organizations and travel service providers to effectively leverage artificial intelligence in developing personalized marketing strategies and enhancing the traveler experience.

The prediction of non-performing loan recovery is one of the main challenges in the banking system. Delays in the timely repayment of loans increase credit risk for banks and undermine their financial health. This study aims to design an accurate, interpretable, and AI-based model to assess the importance of variables influencing the prediction of receivables collection over a 30 to 90-day period. The research methodology is analytical-applied in nature. Real credit and banking data from 750,000 individual customers were utilized, and advanced machine learning algorithms (such as Random Forest and XGBoost), along with explainable artificial intelligence (XAI) methods such as SHAP and LIME, were employed. The results indicated that the algorithms were able to predict delinquent contracts with high accuracy, and SHAP successfully identified variables such as the number of negative months and the average overdue debt in the last three months as the most influential features. The use of explainable artificial intelligence not only preserves the accuracy of predictive models but also enables banking analysts to make decisions based on transparent data interpretation—an element directly contributing to the enhancement of risk management strategies.

This study aimed to identify the contextual and causal factors influencing the sustainable development of professional sports in Iraq. The research employed a qualitative methodology based on the Grounded Theory approach, specifically following Strauss and Corbin’s systematic coding method. Data were collected through semi-structured interviews with 14 purposefully selected experts in the field of sports development, including policymakers, managers, and academics. Snowball sampling was used to ensure the inclusion of diverse perspectives until theoretical saturation was reached. The interviews, ranging from 30 minutes to 2 hours, were transcribed and analyzed in three stages: open coding, axial coding, and selective coding. This process enabled the identification of categories and subcategories contributing to the development of a conceptual model for sustainable sports advancement in Iraq. The analysis revealed two primary dimensions shaping sports sustainability: contextual and causal conditions. Contextual factors included economic resources (oil wealth, corporate investment), geographic advantages (climate and location), human capital (skilled professionals and athletes), public and international policies, and available infrastructure (universities, venues, tourism capacity). Causal factors encompassed public health concerns (inactivity, youth issues), athletic potential (youth fitness, international success), social dynamics (youth interest, inclusion of women and disabled populations), and sports diplomacy (international prestige and cooperation). These interrelated dimensions highlight the importance of strategic planning, institutional alignment, and international engagement. Sustainable development of professional sports in Iraq requires a multidimensional strategy integrating economic planning, human resource investment, infrastructural development, and diplomatic positioning. Iraq’s latent potential can be realized through coordinated efforts that embed sports within national development agendas and foster cross-sectoral collaboration. Emphasis on youth engagement, health promotion, and global visibility is essential to drive long-term success.

This study aims to quantitatively examine the factors affecting the realization of smart government in Iran with an emphasis on the dimensions of digital governance. The research employed a descriptive-correlational survey design and targeted experts and managers in the field of information technology and digital transformation in Iran’s public sector. A structured questionnaire was used to collect data from a sample of 384 participants selected via purposive sampling. The instrument measured constructs such as IT infrastructure, digital governance, organizational agility, digital policymaking, and citizen participation. Data analysis was conducted using SPSS and AMOS software. Structural Equation Modeling (SEM) was employed to test hypothesized relationships and evaluate the measurement and structural models. Inferential statistical analysis using SEM confirmed that all hypothesized relationships were statistically significant at p < 0.001. IT infrastructure (β = 0.804, t = 9.653), comprehensive service delivery (β = 0.308, t = 7.118), choice provision (β = 0.760, t = 9.35), security (β = 0.809, t = 9.39), goal alignment (β = 0.654, t = 12.34), smart services (β = 0.756, t = 7.118), and other factors such as digital governance, digital roadmaps, and smart interaction showed significant positive effects on the realization of smart government. Digital policymaking and digital governance emerged as the strongest predictors. The model’s goodness-of-fit index (GOF = 0.56) indicated a strong overall model fit. The coefficient of determination (R²) for the final structural model was 0.72, demonstrating high explanatory power. The realization of smart government in Iran is significantly influenced by a combination of digital infrastructure, governance mechanisms, policymaking strategies, organizational agility, and civic engagement. Among these, strategic digital policymaking and robust digital governance play pivotal roles. These findings underscore the need for integrated digital strategies and institutional capacity building to support the digital transformation of public administration in Iran.