## 6 Holistic Research Based on Sensory and Consumer Studies
While instrumental methods provide valuable data, they cannot fully replicate sensory experiences' nuanced and subjective nature. A multidisciplinary approach combining instrumental analysis with sensory science is essential for a complete understanding and accurate prediction of human sensory perceptions. Holistic approaches to understanding consumer preferences emphasize integrating multiple factors, including individual, social, cultural, and technological influences. By considering these diverse elements, companies can develop more effective marketing strategies that resonate with consumers' complex decision-making processes. These approaches highlight the importance of a holistic view to capture the dynamic nature of consumer preferences. Recent studies have explored various aspects of this topic. [PERSON] et al. [145] studied marketing strategies for Gen Z. Known as \"digital natives,\" Generation Z exhibits unique consumer preferences influenced by social values, environmental concerns, and sustainability. According to the authors [145], Gen Z relies heavily on social media influencers and prefers personalized experiences, highlighting the importance of marketing strategies that integrate social and technological factors to engage this demographic effectively. On the other hand, the online shopping behaviors of millennial consumers are significantly influenced by cultural and social factors [146]. [PERSON] et al. [146] concluded that understanding these influences allows marketers to develop more effective strategies tailored to this demographic, demonstrating the importance of considering cultural and social dimensions in marketing. [PERSON] [147] examined the role of marketing research in understanding consumer behavior and preferences. The study highlighted how digital channels and social media have changed consumer behavior, underscoring the need for personalized marketing strategies. By leveraging digital analytics and consumer psychology, companies can better understand and influence consumer-brand interactions, integrating technological and psychological marketing factors [147; 148]. [PERSON] and colleagues [149] investigated the effect of marketing strategy on pricing and purchase interest. Their findings revealed that (1) Marketing strategies significantly affect pricing. (2) Marketing strategies do not significantly affect service quality or consumer willingness to purchase. (3) Pricing significantly affects purchase intention, especially when aligned with perceived value. (4) Service quality does not significantly affect purchase intentions. (5) Marketing strategy affects purchase intention through pricing but not through service quality, indicating that service quality is not a potent mediator in this relationship. The interplay between individual traits, social dynamics, cultural norms, and technological innovations significantly shapes consumer behavior. As [PERSON] et al. [148] concluded, marketers must consider these factors when designing effective strategies, highlighting the integration of artistic and technological influences. Big data analytics in digital marketing also allows companies to tailor strategies to individual consumers, increasing customer satisfaction and engagement. This approach integrates technological advances with consumer insights, emphasizing the essential role of technology in understanding consumer behavior [150]. Holistic approaches to understanding consumer preferences require integrating individual, social, cultural, and technological influences. By considering these diverse elements, companies can develop marketing strategies that resonate with consumers' complex decision-making processes, ultimately increasing sales and loyalty. There are three main holistic frameworks and models: (i) The PIE framework--this model considers three primary sources of consumer preferences: the physical attributes of the product (P), individual characteristics of the consumer (I), and external peer group influences (E).