Exploring the role of AI in enhancing sustainability within New Zealand's hospitality industry: A study on knowledge, applicability, and perception in reducing food waste
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Other Title
Authors
Perera, Melanie
Author ORCID Profiles (clickable)
Degree
Master of Applied Management
Grantor
Otago Polytechnic | Te Pūkenga
Date
2024
Supervisors
Alam, Shafiq
Kularatne, Indrapriya
Kularatne, Indrapriya
Type
Masters Thesis
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
sustainability
hospitality industry
food waste
artificial intelligence
perception
New Zealand
hospitality industry
food waste
artificial intelligence
perception
New Zealand
ANZSRC Field of Research Code (2020)
Citation
Perera, M. (2024). Exploring the role of AI in enhancing sustainability within New Zealand's hospitality industry: A study on knowledge, applicability, and perception in reducing food waste. (Unpublished document submitted in partial fulfilment of the requirements for the degree of Master of Applied Management). Auckland International Campus, Otago Polytechnic | Te Pūkenga, New Zealand. https://doi.org/10.34074/thes.6445
Abstract
The hospitality industry in New Zealand is a noteworthy contributor towards the country’s Gross Domestic Product, however, it is also responsible for a significant amount of food waste (FW). In recent years, there has been a growing interest globally in artificial intelligence (AI) to curb FW in the hospitality industry. This study explores the role of AI in reducing FW and enhancing sustainability within New Zealand's hospitality industry, specifically, it focuses on the factors critical for its implementation - knowledge, attitudes, and perceptions of hospitality stakeholders. The study adopted a mixed-methods approach involving quantitative and qualitative data collection from 131 industry professionals.
The data suggests that the sample is skewed towards the lower end of FW, requiring caution due to inconsistent self-reported data with audits (Chisnall, 2017). A quarter were unsure or found it difficult to estimate avoidable food waste (AFW), potentially indicating a lack of awareness or difficulty measuring FW accurately. Inaccurate demand forecasting is the primary cause of FW in catering services and cafes/coffee shops, while portion control and plate waste are cited as the main causes of FW in fine-dining restaurants and pubs. A lack of FW awareness is the leading cause of FW in hotels/resorts and fast-food outlets. The diverse range of challenges faced by the hospitality industry provides insights into the areas where improvements can be made to increase efficiency, reduce waste, and enhance customer satisfaction.
The study found a general lack of awareness and knowledge about AI among hospitality professionals, yet an openness to adopting AI-driven technologies for FW reduction. Challenges such as cost-effectiveness and proven effectiveness are key causes hindering AI adoption. Increased awareness and promotion of AI's return on investment could decrease scepticism and facilitate effective integration into FW reduction strategies. Finally, this research underlines the need for collaborative efforts among industry professionals, policymakers, and technology developers to overcome existing hurdles and leverage AI for sustainable practices in the hospitality sector in New Zealand.
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This thesis is publicly available under a Creative Commons Attribution-NonCommercial-NoDerivatives licence CC BY-NC-ND 4.0 International. This licence applies except where otherwise indicated, especially for images. https://creativecommons.org/licenses/by-nc-nd/4.0/