Processing the right customer information is fundamental for category managers to become more market oriented. Information supply has to respect individual knowledge to support effective information processing and to avoid information overload. The paper investigates mental maps from category managers in order to show how they think in terms of customers. The maps show the relevance and sophistication of customer knowledge on an individual basis. The results indicate that capacity for customer information processing is limited and customer oriented goals play an important role. Market research could improve market orientation of category managers by highlighting very few customer oriented concepts.
Previous research studied the impact of online social cues
(i.e., references on websites to persons or social situations)
on website perceptions. Here, we study whether online
social cues may additionally create a spillover to the
physical channel. We propose that online social cues
on the website attributed to service employees can
strengthen perceived service quality of service employees,
and that the strength of this effect is determined by media
richness. We test our predictions with multisource data
from a sample of 113 service firms, including two samples
of customers for each of the firms. We find that the effects
of online social cues of service employees are strengthened
by the use of rich media, and that online social
cues increase customer loyalty through service quality
perceptions of service employees but not through service
quality perceptions of the website. Thus, the effects of
online social cues are underestimated if their spillover to
physical channels is neglected.
In recent years, interest in the integration and application of neuroscientific theories, concepts, findings and methods to the research discipline of consumer behavior has been increasing. The sub-discipline of consumer neuroscience that has resulted from that interest belongs to the innovative approach of neuroeconomics. Consumer neuroscience investigates problems of consumption and marketing through methods and findings from neuroscience. Conventional research in consumer behavior and marketing necessarily looked at the human organism as being a "black box" which cannot be assessed directly, or physiologically. This was a time when research mainly used theoretical constructs to interpret these bodily processes and resulting behavior. More recently, however, modern techniques and methods in neuroscience have facilitated a far more direct look into the "black box" of the organism as the basis for the sub-discipline of consumer neuroscience. Consumer neuroscience, therefore, can significantly benefit research in the field of consumer behavior, particularly in the attempt to better understand human behavior in decision-making processes. Although consumer neuroscience is a fledgling discipline, it constitutes a complementing advancement toward more comprehensive testing and expansion of theory. Against this background, the primary goal of the paper is to provide an overview of methods, findings, and implications of selected studies in consumer neuroscience. Furthermore, we integrate aspects of consumer policy and neuroethics, discussing the possible implications of these insights for consumer protection.
The integration of both neuroscience and psycho-physiological methods into Information Systems (IS) research in order to better understand how the brain operates in an IS-relevant context has gained importance. Articles highlighting the potential of NeuroIS have opened the discussion of methodological issues associated with the use of fMRI. NeuroIS research, however, must remain cognizant of the fact that the neural implementation of complex mental processes is based on activity in a network of varied brain areas. Against this background, the present article seeks to make a methodological contribution by introducing methods of connectivity analysis to IS research and by giving an overview of the basic principles. We describe different methods of connectivity analysis, discuss a concrete example, and show how connectivity analysis can inform IS research. The major objective of this paper is to contribute to a better understanding of advanced techniques for brain imaging data analysis.
