Clustering the sharing economy in the Philippines: The gaussian graphical approach

Abstract

The study utilizes robust neural network mechanisms to analyse and predict Filipinos’ sharing tendencies of capacity-constrained resources on sharing economy platforms. Specifically, it underscores insights that supplement marketers’ efforts in the peer-to-peer accommodation sector by clustering various groups with their preferred choice of shared resources. The literature answers market related gaps in the implementation of sharing economy enterprises in the tourism industry by advising possible avenues of consolidation. The investigation leads to further discourse by experimenting with demographic level data to split the market into groups for service design and delivery. The paper attempts to contribute to the existing corpus of knowledge by introducing machine learning algorithms in the sharing economy perspective. © the authors, 2021. All Rights Reserved.