How do consumers choose offline shops on online platforms? An investigation of interactive consumer decision processing in diagnosis-and-cure markets

Abstract

PurposeThe purpose of this paper is twofold: (1) to understand the process and consequences of the two-way communication between consumers and businesses on online-to-offline (O2O) diagnosis-and-cure services platforms and (2) to examine how consumer request-specific factors and service quote-specific factors influence consumer decisions in the interactive marketing context.Design/methodology/approachThe study analyzes a dataset of 17,878 service requests and 57,867 price quotes obtained from an O2O platform bridging consumers and automotive repair shops. On the platform, consumers request service quotes by uploading the description of automotive damage and multiple service providers suggest price quotes. The authors formulated a logit model to examine consumer decisions of responding service quotes.FindingsThis paper finds that (1) consumers receiving more severe diagnostic results are more likely to respond to the price quotes, and (2) diagnostic severity and inconsistency moderate the impacts of geographic distance, shop size, and quote price on consumers' responses to the service quotes.Research limitations/implicationsThis paper fills the gap in the literature by advancing the consumer decision processing model to address the interactive shopping experience on O2O diagnosis-and-cure services platforms. The findings are limited by the data and the research context.Practical implicationsFor marketing practitioners, the empirical results imply specific positioning and targeting strategies for markets with informational and geographic barriers to expand the market scope and customer base.Originality/valueThe present work is the first to examine the consumer decision process on O2O diagnosis-and-cure service platforms. It adds value to the literature by investigating how consumers update their problem awareness through the service request-specific factors (i.e. diagnostic severity and diagnostic inconsistency) and how the request-specific factors moderate the impacts of the quote-specific factors (i.e. shop distance, shop size and quote price) on consumers' responses to price quote. The conceptual model and empirical findings provide theoretical and practical values for e-commerce researchers and practitioners.