Integrating Gamification with Demand-Responsive Transportation: An Approach to User-Driven Optimisation
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| Published in: | ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal vol. 14 (2025), p. e32956-e32988 |
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| Main Author: | |
| Other Authors: | , , , |
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Ediciones Universidad de Salamanca
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| Online Access: | Citation/Abstract Full Text - PDF |
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| 001 | 3282913674 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2255-2863 | ||
| 024 | 7 | |a 10.14201/adcaij.32956 |2 doi | |
| 035 | |a 3282913674 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Martí, Pasqual | |
| 245 | 1 | |a Integrating Gamification with Demand-Responsive Transportation: An Approach to User-Driven Optimisation | |
| 260 | |b Ediciones Universidad de Salamanca |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The successful implementation of demand-responsive transportation services is often hindered due to difficulties associated with economic viability. With the aim of reducing service operational costs and environmental impact, this paper proposes an architecture that enables user-driven optimisation through the modification of their travel preferences. Specifically, the paper presents two modules which, integrated with a demand-responsive system, enable vehicle route optimisation, thus saving on costs derived from travelled kilometres and vehicle maintenance. On the one hand, the request modification module computes feasible modifications of the origin or destination stops in a customer travel request, changing them to neighbouring stops such that the transportation routes are simplified. On the other hand, a gamification module is implemented to motivate the customer's acceptance of their request modification. Such a motivation is achieved by offering a personalised reward coupled with each modification, computed taking into account user preferences. Upon the acceptance of a modification, the user receives the reward, which may represent social or monetary benefits within the gamified demand-responsive service. The current research formalises both modules and tests their optimisation potential through the development of a case study in transportation scenarios with variable fleet sizes and demand intensities. The results indicate that the implementation of request modifications can save up to 5 % of a fleet's operational costs if the right conditions are met. Moreover, when the flexibility of the request modification module is increased, savings may increase, however, at the cost of the customer's preferred travel parameters. Thus, a balance between optimisation potential and user satisfaction must be sought. | |
| 653 | |a Customers | ||
| 653 | |a Transportation services | ||
| 653 | |a Modules | ||
| 653 | |a Operating costs | ||
| 653 | |a Cost control | ||
| 653 | |a User satisfaction | ||
| 653 | |a Gamification | ||
| 653 | |a Optimization | ||
| 700 | 1 | |a Jordán, Jaume | |
| 700 | 1 | |a Ðurić, Bogdan Okreša | |
| 700 | 1 | |a Julian, Vicente | |
| 700 | 1 | |a Schatten, Markus | |
| 773 | 0 | |t ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal |g vol. 14 (2025), p. e32956-e32988 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3282913674/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3282913674/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch |