Title:
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ORCHESTRATING TOURISM ACTORS' NETWORK VIA THE "N-1 N+1 TOUCHPOINTS" ALGORITHM: A B2B CHATBOT TO IMPROVE CUSTOMER'S JOURNEYS |
Author(s):
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Randolf Ramseyer, Davide Calvaresi, Benjamin Nanchen, Roland Schegg, Michael Schumacher and Emmanuel Fragnière |
ISBN:
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978-989-8704-26-9 |
Editors:
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Piet Kommers and Pedro Isaías |
Year:
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2021 |
Edition:
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Single |
Keywords:
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Counterfactual Analysis, Customer Journey, Chatbot, Fragmented Touristic Network, Touchpoint, Artificial Intelligence |
Type:
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Short |
First Page:
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314 |
Last Page:
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318 |
Language:
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English |
Cover:
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Full Contents:
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click to dowload
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Paper Abstract:
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This paper elaborates on a novel concept to orchestrate tourism networks. In particular, each actor optimizes his service
(touchpoint n) while seamlessly transferring the customer information from the previous (touchpoint n-1) to the following
service (touchpoint n+1). To implement such a theory, we leveraged on chatbot technology, which interfacing directly
with the user eased the transition from the point of interaction (touchpoint) n-1 to n+1. Moreover, the chatbot entails the
connection between the nodes of the customer's journey, enabling user profiling, personalization, and knowledge transfer.
The deployment of a chatbot implementing the "n-1 n+1 touchpoints" model would significantly benefit actors operating
in a fragmented touristic economy (i.e., Switzerland). Hence, we tested the first prototype in the heart of the Canton
Valais, where, in collaboration with students in tourism, we based the scenario on counterfactual thinking. In particular,
we identified all the possible situations a grandmother and her grandson might face arriving at the Sierre train station to
spend a day in Crans-Montana. In turn, using reenactment theatre techniques, tourism professionals played the worst-case
scenario (without chatbot) and the best case (with the chatbot) to elicit the different clients' perceptions on those
diametral situations. Such a feasibility study paved the way to a more holistic view, employing artificial intelligence
techniques to enhance the chatbot and smoothen the "n-1 n+1 touchpoints" dynamics. |
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