ارائه چارچوب تحلیل عوامل مؤثر بر اجتماعات برند مجازی مبتنی بر فراترکیب با ترکیب پژوهش‌های پیشین

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار، دانشکده مدیریت صنعتی و فناوری، دانشکدگان مدیریت، دانشگاه تهران، تهران ایران.

2 کارشناسی ارشد، دانشکده مدیریت صنعتی و فناوری، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران

3 استاد، دانشکده مدیریت صنعتی و فناوری، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران

10.48311/mri.2026.28891
چکیده
اجتماعات برند مجازی گروهی از حامیان برند هستند که از طریق تعاملات مستمر، تجربیات کاربری، تبلیغات محصولات جدید و ارتباطات اجتماعی، نقش مهمی در تقویت ارزش برند بازی می‌نمایند. این اجتماعات به وفاداری برند، افزایش شناخت برند، و توسعه پایگاه مصرف‌کنندگان کمک کرده‌اند. با وجود پژوهش‌های گسترده در این حوزه، هنوز چارچوب تحلیلی جامعی برای بررسی عوامل موثر بر اجتماعات برند مجازی به گونه نظام‌مند ارائه نشده است. این پژوهش با هدف ارائه چارچوب تحلیلی عوامل مؤثر بر اجتماعات برند مجازی، از روش مرور نظام‌مند و فراترکیب بهره گرفته است. در این راستا، بیش از 1۰۰۰ مقاله بررسی شده و پس از غربالگری در چند گام، ۳2 مقاله مرتبط شناسایی گردیده‌اند. برای گرداوآوری داده‌های از پایگاه‌های داخلی مگیران و SID و پایگاه بین‌المللی اسکوپوس بهره‎گیری شده است. با به‌کارگیری روش فراترکیب سندلوسکی و باروسو برای ترکیب پژوهش‌های پیشین، مفاهیم این حوزه در هفت گام دسته‌بندی شده‌اند. یافته‌های پژوهش نشان می‌دهد که اجتماعات برند مجازی تحت تأثیر 6 توانایی پایه‌ای جای دارند: توانایی بسترساز، توانایی توسعه‌ساز، توانایی محیطی، توانایی درک اجتماعی، توانایی اقدام، و توانایی واکنشی. در نهایت این پژوهش با بهره‌گیری از رویکرد ترکیبی مرور نظام‌مند و فراترکیب، چارچوبی مناسب برای تحلیل عوامل مؤثر بر اجتماعات برند مجازی ارائه داده است. نتایج این پژوهش می‌تواند در شناخت ماهیت اجتماعات برند، بررسی چالش‌ها، تدوین راهبرد‌های مدیریتی، و توسعه‌ی این اجتماعات برای پژوهشگران و مدیران برند راهگشا باشد.

کلیدواژه‌ها

موضوعات

عنوان مقاله English

Providing a framework for analyzing factors affecting virtual brand communities based on meta-synthesis by combining previous research

نویسندگان English

Saghafi Fatemeh 1
Sajad Ramezani 2
ezatollah asgharizada 3
1 University of Tehran
2 Masters degree graduate from the University of Tehran
3 Prof. of University of Tehran
چکیده English

Virtual brand communities are groups of brand supporters who, through continuous interactions, user experiences, promotion of new products, and social communication, play a significant role in enhancing brand value. These communities contribute to brand loyalty, increase brand awareness, and facilitate the expansion of the consumer base. Despite extensive research in this field, a comprehensive analytical framework for systematically examining the factors influencing virtual brand communities has yet to be established. This study aims to develop an analytical framework for the factors affecting virtual brand communities by employing a systematic literature review and meta-synthesis approach. To this end, more than 1,000 articles were examined, and after a multi-stage screening process, 32 relevant studies were selected. Data were collected from the Iranian databases Magiran and SID, as well as the international Scopus database. Using the Sandelowski and Barroso meta-synthesis method to integrate previous studies, the concepts in this domain were categorized through a seven-step process. The findings indicate that virtual brand communities are influenced by six fundamental capabilities: enabling capability, developmental capability, environmental capability, social understanding capability, action capability, and reactive capability. Ultimately, by integrating a systematic literature review with a meta-synthesis approach, this study proposes a comprehensive framework for analyzing the factors influencing virtual brand communities. The results can provide valuable insights for researchers and brand managers in understanding the nature of brand communities, identifying their challenges, formulating managerial strategies, and fostering the development of these communities.

کلیدواژه‌ها English

Virtual brand communities
meta-synthesis
influential factors
brand management framework
strategic analysis
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