Saturday, April 12, 2014

Online consumer behavior modeling

How to attract and win over the consumer in the highly competitive Internet marketplace?

What would the best marketer of the world do?

What would Sun Tzu do? 

What would Alexander the Great do? 

Well, the answer is not so simple, since online consumer behavior has become an emerging research area as well as a key factor for many companies. Digital ecosystems are evolving so rapidly and it seems that even the greatest strategists might face difficulties in consumer behavior modeling and optimizing consumer interactivity with the brand.

But how do we, marketers, approach the construct "online consumer behavior" in the first place? As suggested by Douglas et al. (1994), strong theoretical and conceptual frameworks can be developed through an integration of constructs from different disciplines. It is not coincidental that academic literature on online consumer modeling may be found in Journals like the ones of Electronic Commerce, Marketing Management, Decision Support Systems, Economic Psychology, Interactive Marketing, Management Information Systems and many more. Theory of Reasoned Action (TRA) and its family theories including the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) are dominant theories in process of explaining online consumer actions. Expectation-Confirmation Theory (ECT) and Innovation Diffusion Theory (IDT) have also been repeatedly tested in the study of online consumer behavior.

However, Cheung et al. (2003) tried to approach it by integrating the three key concepts of intention, adoption, and continuance, based on Fishbeins attitudinal theoretical model (Fishbein 1967) and the expectation-confirmation model (Oliver 1980). Their Model of Intention, Adoption, and Continuance (MIAC) seems an interesting framework for developing the framework of their theory.
Thus, the modeling framework proposed, as an extension to Hoffman and Novak (1996), it the following:
The five domains of consumer, product, medium, intermediary characteristics as well as enviromental influences were integrated in MIAC (intention, adoption, repurchase) in order to provide a cohesive view on online consumer behavior.

It seems that a wise marketer may segment the market, target the correct target segment with the correct product, both core and augmented, and position it with the correct marketing mix, in order to win competition. However, medium characteristics should not be ignored; Trust and perceived risk have been widely investigated in the study of consumer online purchase intention. Some recent studies (Lee and Turban 2001) focused primarily on the trust formation process in the context of Internet shopping. Furthermore, environmental influences including norms, cultures and cultural contextual sets should also not be underestimated; A consumer behavior pattern, e.g. adoption and success of a fragrance e-shop in Mexico could be totally different in Greece or India.

Electronic commerce is rapidly changing the way people do business all over the globe. In the B2C segment, Internet sales have been increasing dramatically over the last few years. Customers, not only those from well-developed countries but also those from developing countries, are getting used to the new shopping channel. Understanding the factors that affect intention, adoption and repurchase are important both for researchers and practitioners. MIAC is a nice model to begin with.

Classical consumer behavioral theories provide researchers with a good starting point in understanding online consumer behavior. However, we should take the IT component into serious consideration when doing research in online consumer behavior. Instead of blindly borrowing theories and models from other disciplines, researchers and practitioners should test their own behavioral models declaring what is unique and specific to the context of consumer-based electronic commerce. This may be the only way that marketing can survive in the Digital Age.