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Related Concept Videos

Cognitive Theories: Schachter-Singer Theory of Emotion01:20

Cognitive Theories: Schachter-Singer Theory of Emotion

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Stanley Schachter and Jerome Singer proposed the two-factor theory of emotion, which emphasizes the interplay between physiological arousal and cognitive labeling in forming emotional experiences. This theory suggests that emotions are not simply a result of physiological responses but rather a combination of these responses and the individual's cognitive interpretation of them.
Physiological Arousal and Cognitive Labeling
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Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role...
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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
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The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
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The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
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Related Experiment Video

Updated: Sep 7, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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Prediction Algorithm of User's Brand Conversion Intention Based on Fuzzy Emotion Calculation.

Youwen Ma1

  • 1School of Media and Communication, Shanghai Jiao Tong University, Shanghai, China.

Frontiers in Psychology
|June 20, 2022
PubMed
Summary

Enterprise branding is crucial for international competitiveness. This study reveals how customer involvement and experience value drive customer satisfaction, commitment, and citizenship behavior, offering insights into brand value formation.

Keywords:
brand conversionbrand intentionbrandingfuzzy emotion calculationprediction algorithm

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Area of Science:

  • Business and Management
  • Marketing
  • Brand Strategy

Background:

  • Chinese enterprises face a "big but not strong" dilemma, hindering international brand competitiveness.
  • Existing brand theory research requires strengthening, particularly concerning the mechanisms of enterprise brand value formation.
  • The study addresses the need for empirical analysis on factors influencing corporate brand value.

Purpose of the Study:

  • To investigate the formation mechanisms of corporate brand value.
  • To analyze the influence of customer involvement behavior and customer experience value on customer outcomes.
  • To explore the mediating roles of customer satisfaction and commitment in brand value creation.

Main Methods:

  • Empirical analysis using valid data to examine relationships between key variables.
  • Statistical modeling to assess direct and indirect effects.
  • Application of fuzzy sentiment analysis and an improved ECM-ISC model for brand conversion analysis.

Main Results:

  • Customer involvement behavior positively impacts customer citizenship behavior and experience value.
  • Customer experience value significantly enhances customer satisfaction and commitment.
  • Customer satisfaction and commitment positively influence customer citizenship behavior, with significant mediating effects observed throughout the customer journey.

Conclusions:

  • Customer involvement and experience value are key drivers of brand loyalty and positive customer behaviors.
  • The findings provide actionable insights for enhancing corporate brand value and market positioning.
  • The research contributes to brand economics by examining corporate brand positioning through empirical validation.