EconPapers    
Economics at your fingertips  
 

Artificial Intelligence (AI) and Agritourism: Implications for Entrepreneurial Firms in Emerging Contexts

Patient Rambe () and Mamoipone Elisa Masupa
Additional contact information
Patient Rambe: Central University of Technology, Free State
Mamoipone Elisa Masupa: Central University of Technology, Free State

Chapter Chapter 1 in Agritourism Marketing in Africa, 2025, pp 1-51 from Springer

Abstract: Abstract Even though the promise of Artificial Intelligence (AI) to transform the operations of entrepreneurial firms remains monumental, the coherence of literature on the boundary conditions (i.e. which AI aspects, when and how to deploy them) under which AI could be exploited to enhance agritourism operations is yet to emerge. Drawing on a Systematic Literature Review (PRISMA), the study explored the various components and architecture of AI implementation in agritourism, the conditions under which they are deployed and different AI-embedded strategies that agritourism entrepreneurs use to seize hold of opportunities in the sector. Findings suggest that the widely employed AI components are AI trip forecasting systems, AI-enabled trip generation, trip personalisation and post-trip review techniques. The broad AI architecture used in agritourism spans deep learning forecasting techniques, recommender systems, natural language processing and face recognition, wearable and activity trackers, geotagging, visual navigation, autonomous vehicles, personalisation systems, machine learning and intelligent automation and controlled environments. The conditions under which these are employed involve trip planning (e.g. identifying agritourism locations), trip generation (e.g. choice of mode of transport, payment techniques, activity selection), trip experience (e.g. menu choices, activity participation and experience documentation) and post-trip reviews (e.g. reflections, sentiment analysis, journaling) stages. The paper showcases how agritourism entrepreneurial firms can adopt AI for deepening customer orientation, enhancing customer satisfaction and foregrounding managerial productivity, thereby enriching the theorisation and practice of agriculture, hospitality and tourism sectors.

Keywords: Artificial Intelligence; Agritourism; AI in agritourism (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-78682-2_1

Ordering information: This item can be ordered from
http://www.springer.com/9783031786822

DOI: 10.1007/978-3-031-78682-2_1

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-06-04
Handle: RePEc:spr:sprchp:978-3-031-78682-2_1