Abstract:

Listing spare homes as tourist accommodations on applications like Airbnb has boosted consumers’ adoption of the digital sharing economy (DSE). This research paper aims to develop a variable selection methodology for factors influencing consumers’ adoption intention of DSE applications like Airbnb and UBER. The symmetrical adoption pattern (SAP) will assist industry practitioners in designing an accurate investment pattern for the available resources. The research examines feedback from travellers regarding utilized services to develop SAP. The authors adopt NCapture as a data extraction tool and NVivo 12 as a data analysis tool to develop SAP as a variable selection methodology. Sentiment, thematic, and cluster analysis methods of qualitative analysis were employed to extract 19 distinct variables of SAP out of available data and adapt it into the six constructs of the unified theory of acceptance and use of technology (UTAUT2). By identifying the ideal variable for each construct with SAP, the performed study also aims to broaden the understanding of theories linked to the UTAUT2 model.

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