Service Process Modeling in Practice: A Case Study in an Automotive Repair Service Provider
Source abstract
Abstract
The automotive industry, especially the after-sales service segment, faces significant challenges due to economic changes and market dynamics. In this context, the optimization of service processes becomes essential to increase the performance and profitability of organizations in the industry. However, there is a lack of research that specifically and in detail explores how to model service processes to improve performance in this sector. Most studies focus on general aspects of quality management or process optimization without addressing the particularities of after-sales services in the automotive industry. This paper aims to identify and analyze how to model service processes in an automotive repair service provider organization to increase performance and ensure customer satisfaction. This research was conducted using data from service activity reports and participatory direct observation within an automotive repair service provider organization. Statistical analysis of key performance indicators, such as productivity, efficiency, and customer satisfaction, was performed. This study identified several critical success factors and proposed concrete measures for shaping service processes, including optimizing resource allocation and customer communication, improving customer intake and communication, ensuring technical competence and procedural compliance, and improving the process of handing over and collecting feedback. The implementation of these measures can lead to increased efficiency, customer satisfaction, and, by extension, the financial performance of automotive repair organizations.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Business Process Modeling and Analysis · Service and Product Innovation · Service-Oriented Architecture and Web Services
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Industrial Engineering and Management Department, Faculty of Engineering, “Lucian Blaga” University of Sibiu, 10 Victoriei Street, 550024 Sibiu, Romania
Academy of Romanian Scientist, 3 Ilfov Street, 050094 Bucharest, Romania
Autoklass Center, Chitila Branch, Authorized Mercedes-Benz Sales and Service Center, 103 Rudeni Street, 077045 Chitila City, Romania
Department of Engineering and Technology Management, Faculty of Engineering, Northern University Centre of Baia Mare, Technical University of Cluj-Napoca, 62A Victor Babes Street, 430083 Baia Mare, Romania
References (60)
Show source-provided references
1. Crosby, D.A. (2017). Consciousness and Freedom: The Inseparability of Thinking and Doing, Lexington Books.
2. Collins, J. (2010). Excellence in Business, Curtea Veche Publishing House.
3. Lawler, E., and Boudreau, J.W. (2020). Achieving Excellence in Human Resources Management: An Assessment of Human Resource Functions, Stanford University Press.10.1515/9780804771238 ↗
4. Sevel, C., and Brown, P. (2009). Customers for Life, Public Publishing House.
5. Fader, P. (2020). Customer Centricity: Focus on the Right Customers for Strategic Advantage, University of Pennsylvania Press.10.9783/9781613631010 ↗
6. Role of customers in circular business models10.1016/j.jbusres.2020.12.053 ↗
7. Drucker, P. (2010). Decision and Efficiency, Meteor Press Publishing House.
8. Enhancing emergency department efficiency through simulation and fuzzy multi-criteria decision-making integration10.56578/josa020106 ↗
9. A review on multi-criteria decision-making for energy efficiency in automotive engineering10.1016/j.aci.2018.04.004 ↗
10. Jenson, R. (2010). The Pyramid of Success—Success Organization Through Success People, Codecs Publishing.
11. Metacognitive and metaemotional training strategies through the nine-layer pyramid model of emotional intelligence10.3991/ijes.v9i4.26189 ↗
12. Bohórquez, E., Caiche, W., Benavides, V., and Benavides, A. (2021). Motivation and job performance: Human capital as a key factor for organizational success. Congress in Sustainability, Energy and City, Springer International Publishing.10.1007/978-3-030-94262-5_12 ↗
13. Imai, M. (2005). Kaizen, Public Publishing House.
14. Ohno, T. (2005). Toyota Production System—An Alternative to the Series Production, Finmedia Publishing House.
15. Kaizen and implementation suggestion in the defense industry: A literature review
16. Morell-Santandreu, O., Santandreu-Mascarell, C., and García-Sabater, J. (2020). Sustainability and kaizen: Business model trends in healthcare. Sustainability, 12.10.3390/su122410622 ↗
17. Productivity enhancement and cycle time reduction in toyota production system through jishuken activity—Case study10.1016/j.matpr.2020.06.181 ↗
18. Gil-Vilda, F., Yaguee-Fabra, J.A., and Sunyer, A. (2021). From lean production to lean 4.0: A systematic literature review with a historical perspective. Appl. Sci., 11.10.3390/app112110318 ↗
19. Oprean, C., and Titu, M. (2008). Quality Management in Economy and in the Organization Based on Knowledge, AGIR Publishing House.
20. Fonseca, L., Amaral, A., and Oliveira, J. (2021). Quality 4.0: The EFQM 2020 model and industry 4.0 relationships and implications. Sustainability, 13.10.3390/su13063107 ↗
21. Lăzăroiu, G., Ionescu, L., Andronie, M., and Dijmărescu, I. (2020). Sustainability management and performance in the urban corporate economy: A systematic literature review. Sustainability, 12.10.3390/su12187705 ↗
22. Research on the influence of after-sales service quality factors on customer satisfaction10.1016/j.jretconser.2020.102139 ↗
23. Chen, T., Peng, L., Yin, X., Rong, J., Yang, J., and Cong, G. (2020). Analysis of user satisfaction with online education platforms in China during the COVID-19 pandemic. Healthcare, 8.10.3390/healthcare8030200 ↗
24. Oprean, C., Tîtu, M., and Grecu, D. (2010, January 14–24). The scientific analysis of the competitive advantages provided by the production system Toyota—Just in time. Proceedings of the Asian Conference on the Social Sciences, Osaka, Japan.
25. Milewski, D. (2022). Managerial and economical aspects of the just-in-time system “lean management in the time of pandemic”. Sustainability, 14.10.3390/su14031204 ↗
26. Achieving a just–in–time supply chain: The role of supply chain intelligence10.1016/j.ijpe.2020.107878 ↗
27. Kalbach, J. (2020). Mapping Experiences, O’Reilly Media.
28. Zingraff-Hamed, A., Hüesker, F., Lupp, G., Begg, C., Huang, J., Oen, A., Vojinovic, Z., Kuhlicke, C., and Pauleit, S. (2020). Stakeholder mapping to co-create nature-based solutions: Who is on board?. Sustainability, 12.10.3390/su12208625 ↗
29. Mapping the field of donation-based crowdfunding for charitable causes: Systematic review and conceptual framework10.1007/s11266-020-00213-w ↗
30. Oprean, C., Ţîţu, M., Grecu, D., and Oprean, C. (2011, January 16–18). The Importance of Insuring Document Quality during the Process of Motor Vehicle Repair. Proceedings of the IMECS 2011, Hong Kong, China.
31. Hanafy, M., and Ming, R. (2021). Machine learning approaches for auto insurance big data. Risks, 9.10.3390/risks9020042 ↗
32. Uzair, M. (2021). Who is liable when a driverless car crashes?. World Electr. Veh. J., 12.10.3390/wevj12020062 ↗
33. Oprean, C., Ţîţu, M., and Grecu, D. (2011, January 16–18). Studies and Research on the Possibility of Cost Reduction within the Knowledge-based Organizations in the European Car Industry. Proceedings of the IMECS 2011, Hong Kong, China.
34. Bąk, I., Wawrzyniak, K., and Oesterreich, M. (2022). Competitiveness of the regions of the European Union in a sustainable knowledge-based economy. Sustainability, 14.10.3390/su14073788 ↗
35. Evangelista, P., Kianto, A., Hussinki, H., Vanhala, M., and Nisula, A.M. (2023). Knowledge-based human resource management, logistics capability, and organizational performance in small Finnish logistics service providers. Logistics, 7.10.3390/logistics7010012 ↗
36. Krishnamurthi, R., Kumar, A., Gopinathan, D., Nayyar, A., and Qureshi, B. (2020). An overview of IoT sensor data processing, fusion, and analysis techniques. Sensors, 20.10.3390/s20216076 ↗
37. Posada-Quintero, H.F., and Chon, K.H. (2020). Innovations in electrodermal activity data collection and signal processing: A systematic review. Sensors, 20.10.3390/s20020479 ↗
38. Daniels, A.C. (2007). Managementul Performanţei—Strategii de Obţinere a Rezultatelor Maxime de la Angajaţi, Editura POLIROM.
39. A review: Data pre-processing and data augmentation techniques10.1016/j.gltp.2022.04.020 ↗
40. Design and Implementation of an Integrated Management System for Backfill Experimental Data10.1155/2022/1876435 ↗
41. Munawar, H.S., Qayyum, S., Ullah, F., and Sepasgozar, S. (2020). Big data and its applications in smart real estate and the disaster management life cycle: A systematic analysis. Big Data Cogn. Comput., 4.10.3390/bdcc4020004 ↗
42. Contextual relationships in Juran’s quality principles for business sustainable growth under circular economy perspective: A decision support system approach10.1007/s10479-023-05737-0 ↗
43. Grecu, D. (2011). The Elaboration of the Evaluation Model of the Motor Vehicle’s After Sales Services Level of Quality, Lucian Blaga University. Rapport of the scientific research.
44. Balinado, J.R., Prasetyo, Y.T., Young, M.N., Persada, S.F., Miraja, B.A., and Redi, A.A.N.P. (2021). The effect of service quality on customer satisfaction in an automotive after-sales service. J. Open Innov. Technol. Mark. Complex., 7.10.3390/joitmc7020116 ↗
45. After-sales services and aftermarket support: A systematic review, theory, and future research directions10.1080/00207543.2019.1693655 ↗
46. Ţîţu, M., Oprean, C., and Grecu, D. (2011, January 1–3). Managing the Activity of the After Sales Departments in an Organisation Which Has Implemented a System of Quality Management. Proceedings of the 7th International Conference of the Management of Technological Changes, Alexandropolis, Greece.
47. A systematic literature review of Total Quality Management (TQM) implementation in the organization10.4995/ijpme.2021.13765 ↗
48. Tambare, P., Meshram, C., Lee, C.C., Ramteke, R.J., and Imoize, A.L. (2021). Performance measurement system and quality management in data-driven Industry 4.0: A review. Sensors, 22.10.3390/s22010224 ↗
49. Stawiarska, E., Szwajca, D., Matusek, M., and Wolniak, R. (2021). Diagnosis of the maturity level of implementing Industry 4.0 solutions in selected functional areas of management of automotive companies in Poland. Sustainability, 13.10.3390/su13094867 ↗
50. Public utility vehicle service quality and customer satisfaction in the Philippines during the COVID-19 pandemic10.1016/j.jup.2022.101336 ↗
51. Remedy management for product recalls in the automotive industry: How car dealers should time the repair and communicate its outcome10.1016/j.jbusres.2023.114173 ↗
52. The requisite role of emotional intelligence in customer service in the retail banking sector10.1108/IJOA-04-2022-3229 ↗
53. Managing service recovery experience: Effects of the forgiveness for older consumers10.1016/j.jretconser.2020.102222 ↗
54. Key characteristics of perceived customer centricity in the passenger airline industry: A systematic literature review10.1016/j.jatrs.2024.100031 ↗
55. A quantitative and qualitative study of the link between business process management and digital innovation10.1016/j.im.2020.103413 ↗
56. The impact assessment of smart city policy on urban green total-factor productivity: Evidence from China10.1016/j.eiar.2022.106756 ↗
57. Towards CRISP-ML (Q): A machine learning process model with quality assurance methodology10.3390/make3020020 ↗
58. Explaining black-box classifiers using post-hoc explanations-by-example: The effect of explanations and error-rates in XAI user studies10.1016/j.artint.2021.103459 ↗
59. The impact of customer relationship management and company reputation on customer loyalty: The mediating role of customer satisfaction
60. Cooperation in innovation practices among firms in Portugal: Do external partners stimulate innovative advances?