Akademik Məlumat İdarəetmə Sistemi
Engineering Applications of Artificial Intelligence, vol.162, 2025 (SCI-Expanded, Scopus)
Activist video advertisements represent a strategic form of brand communication in which companies express their stance on social or environmental issues through emotionally driven storytelling and slogan-based narratives. Despite their growing prevalence, there is a notable lack of systematic and quantitative methods for evaluating their performance or comparing their effectiveness across competing brands. This research addresses that gap by proposing a comprehensive decision support system (DSS) designed to assess the performance of activist video advertisements in a structured and reproducible manner. The study introduces a novel hybrid multi-criteria decision-making (MCDM) framework: the spherical cubic fuzzy (SCF)–Aczel-Alsina–ranking comparison (RANCOM)–method based on the removal effects of criteria (MEREC)–deviation-based pairwise assessment ratio technique (DEPART). This methodology integrates subjective weights obtained via SCF–RANCOM and objective weights derived through SCF–MEREC, with both sets of weights combined using SCF-based aggregation operators that incorporate Aczel-Alsina t-norm and t-conorm functions. Performance rankings are then generated using the SCF–DEPART method. To demonstrate the model's applicability, a real-world case study involving eight sustainability-oriented activist video advertisements released in Türkiye was conducted. Evaluations were based on input from ten domain experts across eleven criteria. The analysis identified “convincingness and credibility” as the most critical factor, with “The Voice of Nature” campaign achieving the highest performance rating. The model's robustness was confirmed through scenario-based sensitivity analyses, and its consistency was validated by benchmarking against thirteen alternative MCDM approaches. The findings offer meaningful implications for both academic research and advertising practice.