Dataset of Indicators Related to A Low Carbon Approach Within Energy Saving and Green Waste Management in The Tourism Accommodation Sector.

Published: 8 May 2023| Version 3 | DOI: 10.17632/ky7dc3v5zr.3


This dataset presented a low-carbon approach examination and commitment of hotel operators towards energy saving and green waste management in order to mitigate climate change. The data set provides knowledge and information about the survey on practices of low-carbon approach among hotel managers and staff. The data obtained is useful as a referral among hotel operators in reducing carbon emissions through the practice of energy saving and green waste management. In fact, the data output can be tested for hotel operators entirely in order to transform conventional hotels into low-carbon hotels.


Steps to reproduce

There are several steps in producing the low-carbon approach through energy-saving and waste-management datasets. The survey was performed by using purposive sampling among 19 selected hotels through a questionnaire survey. The data sample inclusion criteria are the accommodation is registered under The Malaysia Ministry of Tourism, Arts and Culture. The data were collected within 4 weeks at the end of November 2022 and the total valid dataset includes 320 samples. The final data gathered was manually keyed in and all the raw data were neatly arranged through a dataset structured in the SPSS. There are four hotel departments involved namely i. Front Office ii. Sales and Administration, iii. Food, Beverage, and Kitchen, and iv. Logistics, Maintenance, Safety, and Housekeeping. The descriptive analysis involved descriptive results of respondents' responses towards practicing energy saving and green waste management in the hotel. Two non-parametric analyses were performed such as the Mann-Whitney U test, to evaluate the differences in low-carbon practices among the manager and staff in the hotel department and the Kruskal-Wallis H test, to see the differences in low-carbon practices for four hotel departments. Data were analyzed using IBM Statistical Package for Social Sciences (SPSS) software version 26.


Universiti Pendidikan Sultan Idris Fakulti Sains Kemanusiaan


Waste Management, Accommodation, Sustainable Tourism, Energy Saving in Building, Hotel Management, Tourism Industry, Climate Change Mitigation Strategies


Ministry of Higher Education, Malaysia