Analyzing the diffusion of competitive smart wearable devices: An agent-based multi-dimensional relative agreement model

Tianyu Zhang, Peiwu Dong, Yongchao Zeng*, Yanbing Ju

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    6 Citations (Scopus)

    Abstract

    Intense innovation competition is increasing products’ complexity. Consumers have to trade off among multiple product attributes before purchasing. Information technologies boost frequent interactions among consumers and lead their opinions to high mutability, which poses challenges for product suppliers. To obtain an in-depth understanding of the diffusion mechanism of emerging technologies in a highly competitive, complex, and dynamic environment, this paper builds an agent-based multi-dimensional relative agreement model and uses smartwatches as a concrete example to analyze their diffusion processes. Three numerical experiments are conducted, respectively focusing on: (1) characteristics of consumer groups; (2) new media marketing strategy; (3) initial expectation management. The results demonstrate: (1) high connectivity with low information uncertainty thresholds benefits product diffusion rate; (2) early promotion and moderate publicity are effective when new media is involved to promote new products; (3) the same initial expectation management strategy may give rise to different diffusion patterns; (4) highly inconsistent consumer opinions hinder product diffusion.

    Original languageEnglish
    Pages (from-to)90-105
    Number of pages16
    JournalJournal of Business Research
    Volume139
    DOIs
    Publication statusPublished - Feb 2022

    Keywords

    • Agent-based modeling
    • Multi-attribute utility theory
    • New product diffusion
    • Relative agreement model
    • Word-of-mouth

    Fingerprint

    Dive into the research topics of 'Analyzing the diffusion of competitive smart wearable devices: An agent-based multi-dimensional relative agreement model'. Together they form a unique fingerprint.

    Cite this