کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
383462 660821 2013 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A novel hybrid social media platform selection model using fuzzy ANP and COPRAS-G
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A novel hybrid social media platform selection model using fuzzy ANP and COPRAS-G
چکیده انگلیسی


• Selecting the right social media platform is a daunting task for marketers.
• Social media platform selection problems are complex multi-criteria problems.
• We propose a novel analytical framework for social media platform selection.
• We integrate the ANP with fuzzy set theory and the COPRAS-G method.
• A case study in airline industry demonstrates the applicability of the framework.

The growing popularity of social media platforms has sparked new marketing opportunities for companies. Marketers have turned to social media campaigns as a means to build brand loyalty, exposure, and engagement. While social media has evolved into a powerful marketing tool, marketers must carefully choose the most suitable social media platform. Improper selection of the social media platform can be costly and can be detrimental to the brand. Despite all of the supposed benefits, selecting the right social media platform has been a daunting task for corporate marketers. The social media platform selection problems are inherently complex problems with multiple and often conflicting criteria. We propose a novel analytical framework for social media platform selection. The proposed hybrid framework integrates the Analytic Network Process (ANP) with fuzzy set theory and the COmplex PRoportional ASsessment of alternatives with Grey relations (COPRAS-G) method. The ANP and fuzzy set theory are used to determine the importance weight of the social media platform selection criteria in a fuzzy environment. The COPRAS-G method is used to rank and select the most suitable social media platform. A case study is presented to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 40, Issue 14, 15 October 2013, Pages 5694–5702
نویسندگان
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