The Role of ChatGPT in Elevating Customer Experience and Efficiency in Automotive After-Sales Business Processes
Abstract
:1. Introduction
Research question: What is the potential role of implementing ChatGPT in streamlining after-sales processes in the automotive sector, particularly in terms of reducing process-completion time?
2. Bibliometric Analysis: Exploring the Application of ChatGPT
3. Methodology
4. Results
4.1. Quantitative Study via Process Mining
4.2. Results of Qualitative Survey with Four Automotive Sector Experts
5. Discussion
6. Conclusions
6.1. Managerial Implications
6.2. Research Limitations
6.3. Future Research
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Database|Index | Web of Science | Scopus | Publish or Perish |
---|---|---|---|
Number of publications | No results | 11 | 15 |
Publication year range | No results | 2022–2023 | 2022–2023 |
Citation overview | No results | 1 | 214 |
Stage | Research Task/s | Research Method/s and Technique/s |
---|---|---|
Stage 1 | Identification of the cognitive gap and formulation of the research question and study objective based on theoretical exploration of the gap and current knowledge regarding the application of ChatGPT in the studied sector. | Bibliometric analysis and literature review, which were based on three knowledge databases and utilized a query related to the keywords “ChatGPT” and “BPM”. |
Stage 2 | Specification of the research-sampling technique and dealership selection criteria. The selection criteria included holding a concession for car maintenance and warranty servicing, being a member of dealership network X, and achieving at least level 3 BPM maturity in the MMPM model process maturity. | Overview of literature on the non-probabilistic technique and purposive sampling. The non-probabilistic sampling technique employed in this study involved the purposeful (non-random) selection of units. The selection criteria primarily focused on units (dealerships) that exhibited a level of BPM maturity corresponding to the level at which processes were measured, and event data were either digitized or recorded in the documentation. This criterion facilitated the reconstruction of process flows and the identification of areas for improvement. |
Stage 3 | Maturity-level verification. Identifying BPM maturity using a research questionnaire based on the MMPM. | Structured interview, using a business process maturity-assessment tool (MMPM model). |
Stage 4 | Analysis of after-sales service documents, including warranty policies and technical documentation. Designing an after-sales process database based on available procedural documentation and reconstructing action sequences with employees of the surveyed units. Compiling an event logs database from the analyzed documentation. | Participant observation. Process mining. |
Stage 5 | Analysis of after-sales service documents, including warranty policies, service orders, warranty claims, and technical documentation. Designing an after-sales process database based on available warranty documentation and reconstructing action sequences with employees of the surveyed units. Compiling an event logs database from the analyzed documentation. Assessing the quality of the obtained data based on the documentation and verifying the data with automotive sector experts. The evaluation of data quality considers not only data gaps but also inconsistencies. Process documentation from the surveyed units was compared with processes reconstructed using process-mining techniques. | CRISP-DM methodology |
Stage 6 | Analysis of the after-sales process, expanding it using the created event logs database. | Process mining |
Stage 7 | Selection of the experts and discussion of the results obtained (mapping the course of the process investigated and activity-implementation timing). | Unstructured interview |
Stage 8 | Identification of the ChatGPT implementation potential in the examined group of processes. Formulation of conclusions, limitations, and further research directions. | Process mining |
ID | Dealership_ID | Mileage | Activity | Actor | Timestamp |
---|---|---|---|---|---|
O12_60 | O_02 | 10,022 | Reception check-out | Service advisor | 27 March 2015 13:55 |
O12_60 | O_02 | 10,022 | Repair end | Technician | 27 March 2015 13:00 |
O12_60 | O_02 | 10,022 | Part transfer to workshop | Parts advisor | 27 March 2015 12:04 |
O12_60 | O_02 | 10,022 | Repair start | Technician | 27 March 2015 11:00 |
O12_60 | O_02 | 10,022 | Service reception | Service advisor | 27 March 2015 9:41 |
O12_60 | O_02 | 10,022 | Repair order printed | Service advisor | 27 March 2015 9:40 |
Activity | Expert | Experts’ Mean Time | Mean in the Process under Study | Median in the Process under Study | |||
---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | ||||
Minutes | |||||||
Service reception -> Repair start | 30 | 25 | 35 | 25 | 29 | 5060 | 55 |
Part transfer to the workshop -> Repair end | Difficult to determine. Depends on the type of repair. | 47 | 48 | ||||
Diagnostic test end -> Repair end | Difficult to determine. Depends on the type of repair. | 51 | 37 | ||||
Repair end -> Reception checkout | 45 | 30 | 30 | 20 | 31 | 1134 | 105 |
Reception check- out -> Claim repair | 1200 | 1500 | 2400 | 3000 | 1775 | 7066 | 6310 |
Activities | Expert 1 | Expert 2 | Expert 3 | Expert 4 |
---|---|---|---|---|
Service Manager (Seniority > 15 Years) | Service Advisor (Seniority > 10 Years) | Workshop Manager (Seniority > 5 Years) | Warranty Auditor (Seniority > 5 Years) | |
Service reception -> Repair start | Customers ask questions which are included in the vehicle’s service book. It should also be noted that there are times when customers do not arrive at the appointed time and thus the technician cannot begin work. | Customers ask for servicing on the day of arrival at the service center. The reception desk, despite the standard, does not always check the actions at the time of appointment reservation by the customer. The large number of minutes between acceptance and repair may result from the fact of receiving the car being in the morning, for example, while the repair is scheduled for the afternoon. | We receive too little information about the defect, which makes its identification a time-consuming task. Additional test drives are needed because of this. | In authorized car service centers, despite the standards, not all information is collected from customers at the time of making an appointment for a repair or inspection. |
Part transfer to the workshop > Repair end | The search for repair instructions incidentally takes time. We have to carry out warranty repairs in accordance with the manufacturer’s guidelines, which is why the technician checks and prints the repair documentation after the parts are released. | Problems with choosing the right repair manual. Not all technicians complete documentation at the diagnosis stage, but rather after receiving the parts. | Limited number of computers, in terms of repair manual and/or technical bulletin search. Internet connection problems emerge at times. The biggest problem in this regard is with new employees, who are not familiar with the systems. | Car service shops do not comply with the standards of repair preparation. Repair documentation should be prepared already at the time of ordering the parts needed to fix the defect. |
Diagnostic test end -> Repair end | The paperwork and bureaucracy involved warranty repairs. The document and report filling out takes more time than the repair in some cases. | In order to meet the requirements of the manufacturer and warranty audits, multi-page repair documentation needs to be compiled, which takes a considerable amount of time. | Diagnosis results need to be checked against the manufacturer’s documentation. Every error (error code) should be checked against the documentation. | The car-service shops’ technicians have to search for solutions to selected codes provided by diagnostic devices. Depending on the repair, some codes refer to specific documentation, while others necessitate a deeper search for errors. |
Repair end -> Reception check-out | The technician must complete the repair report before handing the car over for release. | It is possible that this time range also includes vehicle washing, which is not recorded by many service centers. This means that the time of entering the car wash and completing the task is not recorded on the repair order. | Technicians must compile reports for repairs performed under warranty. Without the inscriptions required by the manufacturer, warranty repairs cannot be claimed. When the descriptions are incomplete, the manufacturer may also refuse to pay for the repair performed. | It is difficult to assess the time range. It would be useful to have additional information regarding the time of the car handover to the service advisor and the car wash, or to make records of such inspection activities as test drives. Keeping records of quality control as part of repair labor time is a standard for some car brands. |
Reception check-out -> Claim repair | The time devoted to compiling the repair documents is unpaid. Particularly expensive repairs, e.g., engine, engine controller, transmission, etc., require a very large number of documents and reports to get the repair accepted and paid for. | Too much information is required to claim a warranty repair. It should be simple enough for any service advisor, as opposed to the need for a highly qualified specialist. | Due to the need to comply with the manufacturer’s standards and warranty policy, each claim is checked times, requiring the participation of employees from different departments. | The execution of warranty audits does not verify the claim-settlement time. There is an upper limit for claim submission. Usually, dealerships first perform the repairs, and only later the repair report is compiled. This is due to the complexity of justifying a warranty repair for claiming purposes. |
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Sliż, P. The Role of ChatGPT in Elevating Customer Experience and Efficiency in Automotive After-Sales Business Processes. Appl. Syst. Innov. 2024, 7, 29. https://doi.org/10.3390/asi7020029
Sliż P. The Role of ChatGPT in Elevating Customer Experience and Efficiency in Automotive After-Sales Business Processes. Applied System Innovation. 2024; 7(2):29. https://doi.org/10.3390/asi7020029
Chicago/Turabian StyleSliż, Piotr. 2024. "The Role of ChatGPT in Elevating Customer Experience and Efficiency in Automotive After-Sales Business Processes" Applied System Innovation 7, no. 2: 29. https://doi.org/10.3390/asi7020029