A holistic methodology for modeling consumer response to innovation

Area of Science:

• Marketing Science
• Consumer Behavior Research
• Quantitative Marketing

Background:

• Existing models for consumer response to innovation have limitations.
• Previous frameworks, such as Hauser and Urban's, do not fully account for measurement error or complex interrelationships.
• There is a need for a more comprehensive model to understand consumer choice behavior in response to new products and marketing efforts.

Purpose of the Study:

• To derive and illustrate a general structural equation model for consumer response to innovation.
• To extend and complement existing models by incorporating measurement error and complex hypothesis testing.
• To provide a framework for modeling the influence of controllable marketing stimuli on consumer choice.

Main Methods:

• Development of a general structural equation model.
• Explicitly accounting for measurement error in consumer response variables.
• Estimation of intercorrelations among exogenous factors.
• Modeling of environmental and managerially controllable stimuli.
• Development of four generic response models.

Main Results:

• The proposed model offers a unique statistical solution and can test complex hypotheses, including simultaneity and feedback loops.
• It explicitly incorporates measurement error, improving the accuracy of consumer response estimation.
• The model allows for the integration of controllable marketing factors (e.g., product design, persuasive appeals) into the analysis of consumer choice.
• Four generic response models are developed to guide the application of the structural equation framework.

Conclusions:

• The derived structural equation model provides a robust and flexible framework for analyzing consumer response to innovation.
• This approach enhances the ability to understand and predict consumer choice behavior by accounting for complex relationships and marketing influences.
• The model and associated response frameworks offer valuable insights for managers aiming to optimize product design and marketing strategies.