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This research aims to examine the impact of Big Data Quality (BDQ) components, including completeness, accuracy, format, and currency, on Big Data-driven Human Resources (BDHRP) management practices and Decision-Making Quality (DMQ) from the viewpoint of HR managers. It also seeks to identify the most impactful components among completeness, accuracy, format, and currency in the context of BDHRP and DMQ. A survey of HR professionals in 108 French organizations deploying Big Data Analytics systems revealed positive relationships between BDQ, BDHRP, and DMQ. Statistical analyses conducted with the Partial Least Squares Structural Equation Modeling (PLSEM) method showed a positive relationship between BDQ components and BDHRP, with currency and accuracy emerging as the most influential factors. Additionally, a strong positive relationship was found between BDQ components and DMQ, with currency and accuracy leading the way. The research also found a significant connection between BDHRP and DMQ, further underscoring the importance of effective HRM practices in enhancing decision-making quality. These findings contribute significantly to understanding the crucial role played by big data quality in BDHRP and decision-making, highlighting the potential for organizations to improve outcomes by focusing on currency and accuracy-related concerns. In practical terms, this research offers insights that can guide data quality practices, resource allocation, and strategic decision-making within organizations.

Purpose: The purpose of this research is to develop a model of export market orientation based on competitive intelligence in the era of the digital economy. Method: This study employed a qualitative approach, utilizing grounded theory as the research method. Sampling was conducted purposefully and continued until theoretical saturation was achieved, involving a total of 15 managers and experts from selected exporting companies. The systematic research process comprised open coding, axial coding, and selective coding, facilitated by strategies such as analysis, questioning, comparison, reminders, schemas, and paradigms. During the coding process, revisions were made, and classifications were validated through feedback from the participants. Findings: The findings revealed the paradigmatic pattern of export market orientation based on competitive intelligence in the era of digital economy including six main categories of causal conditions, context, phenomenon or central category, intervening conditions, strategies and the consequences. Causal conditions have three sub-categories of learning abilities promotion of customer-oriented culture, knowledge of export technology and R&D processes and identification of export market needs; background conditions include three sub-categories of competitive thinking, competitive export processes (technical evaluation) and competitive governance; intervening conditions  include three sub-categories of market technical structure (new technologies), environmental uncertainty and global markets (export risks); the central phenomenon has three sub-categories of value chain (reward strategy), human resource empowerment and employee training (export intelligence); The strategies include three sub-categories of competitive value creation, development of export competitiveness and strategic evaluation of resources and competitive agility and strategic entrepreneurship; The results include three sub-categories of developing entrepreneurial activities, competitive advantage and promoting innovation and dynamic export capabilities. Conclusion: Based on the results, successful implementation of the export market orientation model, grounded in competitive intelligence, requires managers of exporting companies to develop a deeper understanding of the export market. This can be achieved by allocating greater effort to market-oriented activities. Furthermore, by emphasizing competitive intelligence, these companies can improve the perception of their services and create a positive association with their brand in the minds of international customers.

Purpose: The aim of the research was to identify the antecedents and consequences of digital content marketing in online insurance companies.Method: The present study has been conducted by adopting a mixed approach (qualitative and quantitative) and in an exploratory manner. In the qualitative part, thematic analysis technique has been used in the MAXQDA2020 software. The community of the qualitative department was the managers and experts of the sales and marketing department of the insurance industry (electronic and digitalized department). Based on targeted sampling, 10 people were considered as samples. Qualitative data was collected using semi-structured interviews. For the validity of the findings, Cohen's kappa index was 0.837, which is confirmed. Structural equation method is used in a small part. In the quantitative part of the research, the statistical population consisted of experts and managers of marketing units and assistants in the country's insurance industry in Tehran. Using Cochran's formula (for unlimited population), a sample of 384 people was extracted. Based on the codes of the qualitative part, a researcher-made questionnaire was formed. The data collected from the questionnaire were analyzed in AMOS 24 software.Findings: The results show that the antecedents of digital content marketing include the fundamental requirements of digital content marketing, requirements before the production of digital content, managerial/organizational requirements, and perceptual-cognitive antecedents of the audience and identified consequences including marketing consequences, financial consequences, and brand-related consequences, the favorable consequences for the customer and the engagement of the audience with the content in the digital content marketing model.Conclusion: This study has designed and explained the digital content marketing model. In recent years, electronic businesses have been growing rapidly and have gradually taken a relatively favorable share of the industrial enterprises of the country and play an undeniable role in the growth of the country's economy. One of the important parts of digital marketing is the production and creation of valuable content. Another expression, the combination of content and technology refers to the production of digital content. Content marketing is actually a method in which the organization continuously creates and publishes valuable content in order to attract and reach the audience, and its purpose is to transform the customer's behavior into a profitable behavior for the organization.