The impact of perceived benefits and risks on the current and intended levels of big data analytics adoption in hotels

The adoption of big data analytics (BDA) has become prevalent in many business fields due to its various benefits. However, it has been reported that the hospitality industry is reluctant to adopt BDA. Additionally, precedent studies pointed to a knowledge gap and called for further research in this subject. Hence, this research explores the current and intended levels of adoption of BDA in hotels. It also proposes and examines a mediated-moderated model for the impact of perceived benefits and risks on the current and intended levels of BDA adoption in hotels. This study followed a quantitative approach whereby a questionnaire form was developed and distributed to IT managers/engineers and general/deputy managers in hotels. A total of 265 complete and valid responses were collected and analyzed. PLS-SEM using smart PLS 3.0 was employed to test the model. The results indicated that perceived benefits positively influence the current and intended level of BDA implementation in hotels. Moreover, perceived risks had a negative moderating effect on the linkage between perceived benefits and both the current and intended levels of BDA adoption. This study is among the leading studies that have examined the extent to which the perceived benefits and risks of BDA adoption can impact the current and intended levels of BDA implementation in the hotel industry