University of Twente Student Theses
Integration of client choice in the transportation of clients to social care services
Chalkiadis, Theodoros (2025) Integration of client choice in the transportation of clients to social care services.
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| Abstract: | Introduction: This research is focused on the optimisation of patient transportation. Specifically on the client allocation aspect of the transportation process of patients to social care services. Client allocation refers to the allocation of patients to certain care providers or timeslots within the system. Social care services refer to the assistance of people who are unable to independently arrange the care and support they need. This thesis aims to improve the quality perceived by the clients as well as the quality of the company’s specifications. Effective transportation has been proven to have a positive effect on the quality of care provided to clients, hence, it has been selected as the focus point of this thesis. Motivation for the research: The majority of research concerning patient transportation is focused on the optimisation of quantitative variables about the quality of the system concerning distance and time travelled, vehicles used, etc. That, combined with the rising demand for on-demand transportation, raises significant concerns about the quality of the transportation process perceived by the patients. Research objective and research questions: This research aims to identify the trade-off between client choice (CC) and system efficiency in the field of patient transportation. Client choice refers to the ability of clients to choose between several care providers (CPs). The objective is to determine the most effective way to increase customer-based quality, without compromising on the technical efficiency of the system. To complete this objective, the following research questions have been formulated. Main Research Question: “What is the trade-off between client choice and transportation costs in the client allocation phase of patient transportation?” Sub-Questions: 1. What is the current strategy for allocating and transporting patients to care providers? 2. How is client choice known to be modelled in a DARP? 3. How should the client allocation model be constructed? 4. What is the performance of the strategies concerning the selected KPIs? Approach: The context of the transportation system can me modelled as a Dial-a-ride problem (DARP). Because of the limited literature on client allocation models in a DARP, especially including the integration of client choice in the model, there was a liberty in the research approach. Initially, the variable that should be subject to client choice was decided. After the care provider (CP) was selected as the variable to be subject to client choice, the model was constructed. The case was modelled by using Integer Linear Programming (ILP). Three strategies for client allocation were constructed, in which the criteria for which care provider was subject to client choice differed, as well as the objective. The Shortest Distance Strategy populates Πi with the CPs closest to client i. The Availability strategy has the same objective but takes an extra variable, the availability of each client. For those two strategies, the objective is the distance between client and CP. The Rating strategy’s objective is to minimise the product of the distance of a CPs to client i, and the CP’s rating. The model optimises the timeslot(s) and care provider a patient is allocated to. Every strategy has four variants, distinguished by the number of care providers subject to client choice (2-4). Then, the results are assessed by using them as input to a routing algorithm that ultimately calculates the total time travelled. Results: After several experiments, the three strategies and their variants were compared on the total time travelled. Besides the travel time, the standard deviation and a 97,5% confidence interval were identified for every experiment. The table below presents the time travelled in minutes for all the variants of the three strategies. The results show a negative correlation of CPs subject to client choice and time travelled. The only variant that opposes this conclusion is the variant of 2 CPs of the rating strategy. Likely, because of the random element implemented in the variable of the CP’s rating, in the rating strategy. Every strategy’s most efficient variant is the one with 5 CPs subject to CC. Additionally, the best�performing strategy is the Availability of 5 CPs subject to CC with a travel time of 25.025,2 minutes. Outlook: Future research can be done on the effects of having other variants subject to CC. Timeslots and means of transportation (taxi, shared transportation, etc.) can be some of them. Additionally, there can be a more detailed measurement of perceived quality from the customers’ and care provider’s perspective. The impact of the quality of the system with the increase of the CPs subject to CC can be specifically determined. |
| Item Type: | Essay (Bachelor) |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 55 traffic technology, transport technology |
| Programme: | Industrial Engineering and Management BSc (56994) |
| Link to this item: | https://purl.utwente.nl/essays/105153 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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