An Empirical Comparison of Consumer Innovation Adoption Models: Implications for Subsistence Marketplaces

So called “pro-poor” innovations may improve consumer wellbeing in subsistence marketplaces. However, there is little research that integrates the area with the vast literature on innovation adoption. Using a questionnaire where respondents were asked to provide their evaluations about a mobile banking innovation, this research fills this gap by providing empirical evidence of the applicability of existing innovation adoption models in subsistence marketplaces. The study was conducted in Bangladesh among a geographically dispersed sample. The data collected allowed an empirical comparison of models in a subsistence context. The research reveals the most useful models in this context to be the Value Based Adoption Model and the Consumer Acceptance of Technology model. In light of these findings and further examination of the model comparison results the research also shows that consumers in subsistence marketplaces are not just motivated by functionality and economic needs. If organizations cannot enhance the hedonic attributes of a pro-poor innovation, and reduce the internal/external constraints related to adoption of that pro-poor innovation, then adoption intention by consumers will be lower

Flying to Quality: Cultural Influences on Online Reviews

Customers increasingly consult opinions expressed online before making their final decisions. However, inherent factors such as culture may moderate the criteria and the weights individuals use to form their expectations and evaluations. Therefore, not all opinions expressed online match customers’ personal preferences, neither can firms use this information to deduce general conclusions. Our study explores this issue in the context of airline services using Hofstede’s framework as a theoretical anchor. We gauge the effect of each dimension as well as that of cultural distance between the passenger and the airline on the overall satisfaction with the flight as well as specific service factors. Using topic modeling, we also capture the effect of culture on review text and identify factors that are not captured by conventional rating scales. Our results provide significant insights for airline managers about service factors that affect more passengers from specific cultures leading to higher satisfaction/dissatisfaction