The diffusion process of an innovation, whether it be a product, a service or an idea, will vary in function of the characteristics of that innovation, as well as of the agents to whom it is directed. The objective of this paper is to differentiate the behaviour of the different adopter categories that emerge at the time of the adoption of new products. Uses the methodology proposed by Mahajan et al., based on the Bass model, which allows for a distinction to be drawn between five categories of adopters, namely innovators, early adopters, early majority, late majority and laggards, with reference to the acceptance process for new consumer durables. This is employed in an empirical application carried out with respect to the adoption of various consumer durables that are frequently found in the majority of households, whilst the demographic and socio‐economic characteristics of the individuals who make up each adopter category are used in order to differentiate their behaviour.
Managing the increasing number and complexity of customer-initiated interactions across multiple channels consistently and effectively has become a key priority for marketing academics and practitioners. To achieve this, it is imperative that marketers understand how and why customers choose the available channels. In this study, we distinguish between two types of interactions, purchases and communications, and argue that the nature of these interactions influences the way customers behave in the presence of multiple channels. Drawing upon perceived risk research, this study develops an integrated conceptual framework that provides a theoretical understanding of customer channel choice for these interactions. The framework is tested empirically in financial services and the results reveal that channel choices significantly differ for purchases and communications. Channel choices for purchases are more inertial and more strongly affected by attitudes (i.e., relationship quality) than for communications. At the same time, preference for a personal touch in channel choice is more pronounced for purchases than for communications, and marketing activities are more effective at driving channel choice for communications. These results offer some recommendations for managing interactions across channels more effectively. For example, the use of personal channels is advised for managing high-risk interactions (i.e., purchases), while for low-risk interactions (i.e., communications), firms can use marketing activities to migrate customers to cheaper channels.
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