نوع مقاله : مقاله پژوهشی
نویسندگان
1 استاد، دانشکده اقتصاد، مدیریت و علوم اداری دانشگاه سمنان، سمنان، ایران نویسنده مسئول: feiz1353@semnan.ac.ir
2 استاد، دانشکده اقتصاد، مدیریت و علوم اداری دانشگاه سمنان، سمنان، ایران
3 دانشجوی دکتری ، دانشکده اقتصاد، مدیریت و علوم اداری دانشگاه سمنان، سمنان، ایران
4 دانشجوی دکتری، دانشکده اقتصاد، مدیریت و علوم اداری دانشگاه سمنان، سمنان، ایران
چکیده
پژوهش حاضر به بررسی تأثیر هوش مصنوعی بر ارز اجتماعی در بازاریابی دیجیتال میپردازد. با تحول مفاهیمی مانند هویت، تعلق و وفاداری توسط فناوریهای هوشمند، این مطالعه ابعاد نوظهور ارز اجتماعی را تحلیل کرده و چارچوبی نوآورانه برای بهینهسازی استراتژیهای بازاریابی در عصر هوش مصنوعی ارائه میدهد. تمرکز اصلی بر نقش هوش مصنوعی در شخصیسازی، پیشبینی رفتار و تولید محتوا است که موجب دگرگونی ارزشهای ناشی از تعاملات اجتماعی دیجیتال شده است. این پژوهش با روش کیفی و تحلیل تم انجام شد. دادهها از طریق مصاحبههای نیمهساختاریافته با 16 متخصص در حوزههای بازاریابی، مدیریت و هوش مصنوعی جمعآوری و پس از کدگذاری، تحلیل شدند. فرآیند تحلیل منجر به شناسایی 140 کد اولیه، 20 مضمون سازماندهنده و 5 مضمون اصلی شد که شامل: تحول ارزشهای اجتماعی در فضای دیجیتال، نقش هوش مصنوعی در توسعه سرمایه اجتماعی، تأثیر هوش مصنوعی بر رفتار مصرفکننده، استحکام روابط بلندمدت با مشتریان و تسریع تعاملات دیجیتال بودند. یافتهها نشان میدهند که هوش مصنوعی با بازتعریف ابعاد ارز اجتماعی، تعاملات دیجیتال را غنی کرده و ابزارهایی برای پیشبینی رفتار و تقویت وفاداری ارائه میدهد. با این حال، چالشهایی مانند نقض حریم خصوصی، تعصبات الگوریتمی و کاهش لمس انسانی از موانع اصلی هستند. این پژوهش پیشنهاد میکند که شرکتها با پیادهسازی سامانههای تحلیل داده، برگزاری دورههای آموزشی و تدوین چارچوبهای اخلاقی، این چالشها را مدیریت کنند تا از مزیتهای هوش مصنوعی بهرهمند شوند.
کلیدواژهها
موضوعات
عنوان مقاله [English]
Analyzing the Dimensions of Social Currency in the Digital Marketing Ecosystem: Based On Artificial Intelligence
نویسندگان [English]
- Davood Feizِ 1
- Azim Zarei 2
- Mohsen Arman 3
- Elham Sadat Kia 4
1 Professor, Faculty of Economics, Management and Administrative Sciences Corresponding Author: feiz1353@semnan.ac.ir
2 Professor, Faculty of Economics, Management and Administrative Sciences
3 Ph.D. Student, Faculty of Economics, Management and Administrative Sciences
4 Ph.D. Student, Faculty of Economics, Management and Administrative Sciences
چکیده [English]
This study examines the impact of artificial intelligence (AI) on social currency in digital marketing. By transforming traditional concepts such as identity, belonging, and loyalty through intelligent technologies, this research analyzes emerging dimensions of social currency and proposes an innovative framework for optimizing digital marketing strategies in the AI era. The primary focus is on AI's role in personalization, behavior prediction, and content generation, which has revolutionized the value derived from digital social interactions .Using a qualitative methodology and thematic analysis, data were collected through semi-structured interviews with 16 experts in marketing, management, and AI. The analysis process identified 140 initial codes, 20 organizing themes, and 5 overarching themes: transformation of social values in digital spaces, AI's role in developing social capital, AI's influence on consumer behavior, strengthening long-term customer relationships, and accelerating digital interactions. Findings indicate that AI enriches digital interactions by redefining social currency dimensions and providing tools for behavior prediction and loyalty enhancement. However, challenges such as privacy violations, algorithmic biases, and reduced human touch remain significant barriers. The study recommends that companies implement data analytics systems, conduct training programs, and establish ethical frameworks to manage these challenges and leverage AI's benefits.
کلیدواژهها [English]
- Social Currency
- Thematic Analysis
- Digital Marketing
- Artificial Intelligence
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استناد به این مقاله: فیض، داود.، زارعی، عظیم.، آرمان، محسن.، سادات کیا، الهام. (1404). تحلیل ابعاد ارز اجتماعی در اکوسیستم بازاریابی دیجیتال: مبتنی بر هوشمصنوعی، مطالعات مدیریت کسب وکار هوشمند، 14(54)، 85-120. DOI: https://doi.org/10.22054/ims.2025.86242.2625
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