Artificial Intelligence and Startup Development: An Empirical Examination of Airbnb’s Performance Indicators
Keywords:
Startups, Artificial Intelligence, Platform Economy., Performance Measurement, AirbnbAbstract
Objectives: The study investigates whether AI adoption impacted Airbnb’s financial results through its key performance indicators. Prior Work: AI business research has grown rapidly but most studies remain theoretical because researchers have not conducted quantitative studies that compare AI adoption through multiple business milestones. Approach: The study uses a comparative design to study two time periods during which it examined seven different performance metrics between 2015–2016 and 2017–2018. Backlinko provides the quantitative data which researchers used descriptive statistics and Paired-Samples T-tests for analysis through SPSS software. Results: The post-AI period exhibited higher growth rates for all indicators when compared to the pre-AI period. The three indicators which reached statistical significance at α = 0.05 were nights and experiences booked (p = 0.030) and product development expenditure (p = 0.049) and sales-and-marketing expenditure (p = 0.026). The four remaining effects demonstrated substantial practical implications which nearly reached the threshold because the paired sample contains only two data points per group. Implications: Entrepreneurs must establish AI deployment budgets because their business expenses will start before their technology benefits. Value: The paper establishes a replicable framework for studying technology adoption impacts in fast-growing businesses through its examination of AI effects on company financial records instead of survey results.
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