The Analysis of the Consequences of Product Pricing Structures on Product Evaluations

Abstract

The purpose of this paper is to contribute to the literature and practice by examining the effect of product pricing on consumer behaviours with regard to the assertiveness and the sentiments expressed in their product reviews. Using web crawling techniques, a large dataset was extracted from the Google Play Store. Following this, we created a machine learning tool to identify topics from product reviews and to quantify assertiveness and sentiments from the review texts. Our results indicate that product pricing models affect consumer review sentiment, assertiveness and topics. Removing upfront payment obligations positively impacts the overall and pricing specific consumer sentiment and reduces assertiveness. The results reveal new effects of pricing models on the nature of consumer reviews of products and form a basis for future research. Our findings can help companies that create digital products in choosing a pricing strategy for their apps. The paper is first to investigate how pricing modes affect the nature of online reviews written by the consumers. In addition, the paper uses new data collection and machine learning tools that can also be extended for other research of online consumer reviewing behaviors.