The impact of the green Internet of Things on hotel environmental performance: does green digital learning help?
Hooshmand Bagheri Garbollagh et al.
Abstract
Purpose Green Internet of Things (green IoT) exhibits a positive association with circular economy practices (CE practices), which, in turn, contribute to improved hotel environmental performance (HEP). Given the global imperative to shift from a linear economy to a more sustainable CE, it is crucial to investigate the role of green IoT technology in facilitating this transition. To address this gap, the purpose of this study is to examine the impact of green IoT on HEP, considering the mediating effects of CE practices and servitization, as well as the moderating influence of green digital learning (green DL). Design/methodology/approach This research is based on applied research objectives and data collection methods; it is descriptive and correlational. Online questionnaires were used to collect data from a targeted sample (n = 278) comprising managers and employees at various levels in four- and five-star hotels in the city of Urmia. These service organizations included Ana, Sahel, Deniz, Ariya and Jahangardi hotels. The structural equation modeling method and Smart-PLS3 software were used to test the hypotheses. Findings The research results indicate that green IoT technology significantly affects CE and servitization. Furthermore, the findings of this study reveal a significant relationship between CE, servitization and HEP. The moderating role of green DL in the relationship between green IoT, CE and servitization was also confirmed. Originality/value To the best of the authors’ knowledge, this study is the first to integrate green DL with variables such as green IoT, CE, servitization and environmental performance in the hospitality industry.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.