Interactive music for multisensory e‐commerce: The moderating role of online consumer involvement in experiential value, cognitive value, and purchase intention

Citations Over TimeTop 10% of 2020 papers

Abstract

Abstract Background music adds a multisensory element to marketing and e‐commerce. Applying interactive sensory‐enabling technologies (SETs) to online shopping websites is an area of interest in sensory marketing. This research examines interactive background music in e‐commerce and investigates how online consumer involvement moderates the effects of interactive music. Single‐factor experiments with three conditions (interactive music, static background music, and control) were conducted to investigate its impact on experiential value, cognitive value, and purchase intention of high‐ and low‐involvement consumers among both students (Study 1, N = 251) and nonstudent samples (Study 2, N = 218). Different music genres were applied to stimuli of the two studies to demonstrate the generalizability of the findings. Results find that interactive music enhances the experiential value of e‐commerce for low‐involvement consumers. By contrast, high‐involvement consumers show greater purchase intention under the interactive music condition due to a heightened level of perceived cognitive value. Involvement is an effective predictor of elaboration and purchase intention under the interactive music condition, but not under the other two conditions. The contribution is twofold: (a) it shows the impact of music as an interactive SET and, (b) demonstrates the moderating role of consumer involvement in the context of multisensory integration in e‐commerce. Theoretical and practical implications are discussed along with limitations and directions for future research.

Related Papers

• → Generalizing Generalizability in Information Systems Research(2003)1,544 cited
• → Generalizability theory: a primer(1992)1,325 cited
• → Applying Generalizability Theory using EduG(2011)108 cited
• → Extending generalizability theory to single-subject designs(1979)7 cited
• → Using Generalizability Theory for the Estimation of Reliability of a Patient Classification System(1994)1 cited