A multi-criteria intelligence aid approach to selecting strategic key opinion leaders in digital business management - H. Y. Lam; V. Tang; C. H. Wu; V. Cho (Journal of Innovation & Knowledge (JIK), 2024)
In the wake of the global disruption caused by the coronavirus pandemic, digital channels have emerged as a significant driver of business sales. As such, the value of digital business management has received considerable attention from industrial practitioners. Beyond conventional promotion techniques, collaboration with digital market influencers has shown significant potential for business organisations by creating a circle of trust. However, managing influencers in the business-to-business market is far more complex than in business-to-consumer markets, as it involves balancing business processes, competitive advantages, company image and risks rather than solely motivating customer engagement. It is, therefore, critical for organisations to carefully select key opinion leaders (KOLs). To address this challenge, this study introduces an intelligent multi-criteria KOL analytics framework that embeds the fuzzy best-worst method and the fuzzy technique for order preference by similarity to the ideal solution. The framework converts subjective and linguistic criteria, determines the attribute most relevant to the business, and then selects the most suitable KOLs for the campaign. A case study was conducted in partnership with a digital marketing agency in Hong Kong to demonstrate the feasibility and advantages of this approach. This model facilitates the evolution of digital business management by systematically identifying and assessing KOLs, contributing to significant changes in the digital business environment for companies.
Keywords: D80; D81; 650; Digital business management; Key opinion leaders; Business-to-business; Artificial intelligence; Multi-criteria decision-making