A review on Mahalanobis-Taguchi system and time-driven activity-based costing for production environment
Keywords:
Capacity utilization, Degree of contribution, MTS, TDABCAbstract
Mahalanobis-Taguchi system (MTS) is a decision-making system that identifies patterns. The fundamental idea of MTS is to select a set of variables and then apply Mahalanobis distance to optimize each of the factors that contribute to the issue. Meanwhile, time-driven activity-based costing (TDABC) is an approach that defined as a costing model that provides the cost of activities based on the amount of time consumed per activity. The current study seeks to address several gaps and presents research motivation with a particular focus on the potential benefits that comes from employing these two approaches individually in a variety of disciplines. The content of this paper generally consists of studies of literature from 2013 to 2023 from the fields of agriculture, industrial, communication, education, health care, hospitality, and finance sectors. To begin, 74 and 140 research publications employing MTS and TDABC, respectively, have been discovered. From the findings, the industrial sector has the greatest proportion of using MTS technique with 60.81% for 45 from overall 74 articles. MTS is widely used in production environment, as it is a powerful method of optimization that revealed the criticality of parameters, thus can reduce the rejected product in a process. Whereas the health care industry has the largest percentage of articles using the TDABC approach in cost accounting systems, with 62.14% for 87 from total 140 articles. TDABC is popularly applied in health care primarily to estimate the cost of clinical procedures and visits in order to inform operational improvement.
References
Cheng, L., Yaghoubi, V., Paepegem, W.V., and Kersemans, M. “On the Influence of Reference Mahalanobis Distance Space for Quality Classification of Complex Metal Parts Using Vibrations.” Applied Sciences 10, no. 23 (2020): 8620. https://doi.org/10.3390/app10238620.
Sakeran, H., Osman, N.A.A, Majid, M.S.A, Mustafa, W.A., and Idrus, S.Z.S. “Gait Analysis with Kanri Distance Calculator Following Anterior Cruciate Ligament Reconstruction.” Journal of Physics: Conference Series 1529, (2020): 042015. https://doi.org/10.1088/1742-6596/1529/4/042015.
Al-Amiri, N, and El-Khmidi, S. “Implementing Time-Driven Activity-Based Costing (TDABC) in Out-Patient Nursing Department: A Case from UAE.” Management Science Letters 9, no. 3 (2019): 365–80. https://doi.org/10.5267/j.msl.2018.12.012.
Altawati, N.O.M., Ng, K.S., Ahmad, A.R., and Elmabrok, A.A. “A Review of Traditional Cost System versus Activity Based Costing Approaches.” Advanced Science Letters 24, no. 6 (2018): 4688–94. https://doi.org/10.1166/asl.2018.11682.
Bruns, W.J., and Kaplan, R.S. Accounting & Management : Field Study Perspectives. Boston, United States: Harvard Business School Press, 1987.
Kaplan, R.S., and Anderson, S.R. “Time-driven activity-based costing.” White Paper presented at the First European Summit on Time-Driven Activity-Based Costing, 2003.
Kamil, N.N.N.M., Zaini, S.N.A.M., and Abu, M.Y. “A case study on the unused capacity assessment using time driven activity based costing for magnetic components.” International Journal of Industrial Management 6, no. 1 (2020): 18-39. https://doi.org/10.15282/ijim.9.0.2021.5954.
Peng, Z., Cheng, L., Yao, Q., and Zhou, H. “Mahalanobis-Taguchi system: A systematic review from theory to application.” Journal of Control and Decision 9, no. 2 (2022): 139-151. https://doi.org/10.1080/23307706.2021.1929525.
Mao, T., Yu, L., Zhang, Y., and Zhou, L. “Modified Mahalanobis-Taguchi System based on proper orthogonal decomposition for high-dimensional-small-sample-size data classification.” Mathematical biosciences and engineering : MBE 18, no. 1 (2020): 426–444. https://doi.org/10.3934/mbe.2021023.
Peng, X.H., Zheng, R., and Liu, J.F. “Feature Selection for Mahalanobis-Taguchi System with Chaotic Quantum Behavior Particle Swarm Optimization.” International Conference on Computer Science, Communications and Multimedia Engineering (CSCME 2019). https://doi.org/10.12783/dtcse/cscme2019/32535.
Peng, Z., Cheng, L., and Yao, Q.F. “Multi-Feature Extraction for Bearing Fault Diagnosis Using Binary-Tree Mahalanobis-Taguchi System,” Chinese Control And Decision Conference (CCDC), Nanchang, China (2019): 3303-3308. https://doi.org/10.1109/ccdc.2019.8832374.
Gu, Y., Cheng, L., and Chang, Z. ”Classification of imbalanced data based on MTS-CBPSO method: A case study of financial distress prediction.” Journal of Information Processing Systems (JIPS) 15, no. 3 (2019): 682-693. https://doi.org/10.3745/jips.04.0119.
Abu, M.Y., Norizan, N.S., and Rahman, M.S,A. “Integration of Mahalanobis-Taguchi System and Traditional Cost Accounting for Remanufacturing Crankshaft.” IOP Conference Series: Materials Science and Engineering 342, (April 2018): 012005. https://doi.org/10.1088/1757-899x/342/1/012005.
Muhamad, W.Z.A.W., Jamaludin, K.R., Zakaria, S.A., Yahya, Z.R., and Saad, S.A. “Combination of feature selection approaches with random binary search and Mahalanobis Taguchi System in credit scoring.” Proceeding of the 25th National Symposium on Mathematical Sciences (SKSM25) 1974, no. 1 (2018): 020004. https://doi.org/10.1063/1.5041535.
Ordikhani, S., and Habibi, S. “Feature selection in big data by using the enhancement of Mahalanobis-Taguchi System case study: Identifiying bad credit clients of a private bank of Islamic Republic of Iran.” Journal of Modern Processes in Manufacturing and Production 7, no. 3 (2018): 29-44.
Muhamad, W.Z.A.W., Jamaludin, K.R., Ramlie, F., Harudin, N., and Jaafar, N.N. “Criteria Selection for an MBA Programme Based on the Mahalanobis Taguchi System and the Kanri Distance Calculator.” In IEEE 15th Student Conference on Research and Development (SCOReD), Wilayah Persekutuan Putrajaya, Malaysia, p. 220-223. 2017. https://doi.org/10.1109/scored.2017.8305390.
Reséndiz-Flores, E., and López-Quintero, M. “Optimal identification of impact variables in a welding process for automobile seats mechanism by MTS-GBPSO approach.” International Journal of Advanced Manufacturing 90, (2017): 437–443. https://doi.org/10.1007/s00170-016-9395-5.
Keel, G., Savage, C., Rafiq, M., and Mazzocato, P. “Time-Driven Activity-Based Costing in Health Care: A Systematic Review of the Literature.” Health Policy 121, no. 7 (2017): 755–763. https://doi.org/10.1016/j.healthpol.2017.04.013.
Mahmood, S.; and Sabir, R.A. “The impact of time driven activity based costing on competitive advantage in the Kurdistan Region of Iraq economic unit.” Journal of Harbin Engineering University 44, no. 5 (2023): 121-139.
Erkek, İ.B., Adıgüzel, H., and Türüdüoğlu, F.O. (2022). Time driven activity based costing system implementation in the internal audit department of a bank. Muhasebe Bilim Dünyası Dergisi, Special Issue of MODAV's 18th International Conference on Accounting 24, (2022): 86-109. https://doi.org/10.31460/mbdd.1060410.
Mohsin, N.M.R., Al-Bayati, H.A.M., and Oleiwi, Z.H. “Product-Mix Decision Using Lean Production and Activity-Based Costing: An Integrated Model.” The Journal of Asian Finance, Economics and Business 8, no. 4 (2021): 517–527. https://doi.org/10.13106/jafeb.2021.vol8.no4.0517.
Dubron, K., Verschaeve, M., and Roodhooft, F. “A time-driven activity-based costing approach for identifying variability in costs of childbirth between and within types of delivery.” BMC Pregnancy Childbirth 21, (2021): 705. https://doi.org/10.1186/s12884-021-04134-4.
Karabachev, A.D. et al. “Outcomes in patients with and without intraoperative parathyroid hormone testing for primary hyperparathyroidism: A retrospective observational analysis.” Perioperative Care and Operating Room Management 23, (2021): 100157. https://doi.org/10.1016/j.pcorm.2021.100157.
Kamil, N.N.N.M., Abu, M.Y., Zamrud, N.F., and Safeiee, F.L.M. “Analysis of magnetic component manufacturing cost through the application of Time-Driven Activity-Based Costing.” In iMEC-APCOMS 2019, LNME, p. 74–80. 2020. https://doi.org/10.1007/978-981-15-0950-6_12.
Zubek, M. “The role of management information in education management.” Public Governance 2, no. 52 (2020): 39-50. https://doi.org/10.15678/ZP.2020.52.2.04.
Andalya, E., Lesetedi, L., and Mohee, R. “Application Of Time-driven Activity-based Costing In Botswana Open University.” In Pan – Commonwealth Forum, Edinburgh Scotland, p. 1-9. 2019.
Park, Y., Jung, S., and Jahmani, Y. “Time-driven activity-based costing systems for marketing decisions.” Studies in Business and Economics 14, no. 1 (2019): 191-207. https://doi.org/10.2478/sbe-2019-0015.
Kamil, Nik Nurharyantie Nik Mohd, Sri Nur Areena Mohd Zaini, and Mohd Yazid Abu. “Feasibility Study on the Implementation of Mahalanobis-Taguchi System and Time Driven Activity-Based Costing in Electronic Industry.” International Journal of Industrial Management 10, no. 1 (2021): 160–172. https://doi.org/10.15282/ijim.10.1.2021.5982.
Ostadi, B., Daloiea, R.M., and Sepehri, M.M. “A combined modelling of fuzzy logic and time-driven activity-based costing (TDABC) for hospital services costing under uncertainty.” Journal of Biomedical Informatics 89, (2018): 11–28. https://doi.org/10.1016/j.jbi.2018.11.011.
Goense, L. et al. “Hospital costs of complications after esophagectomy for cancer.” European Journal of Surgical Oncology 43, no. 4 (2017): 696-702. https://doi.org/10.1016/j.ejso.2016.11.013.
Hamid, K.S. et al. “Determining the cost-savings threshold and alignment accuracy of patient-specific instrumentation in total ankle replacements.” Foot & Ankle International 38, no. 1 (2017): 49-57. https://doi.org/10.1177/1071100716667505.
Helmers, R.A. et al. “Overall cost comparison of gastrointestinal endoscopic procedures with endoscopist- or anesthesia-supported sedation by activity-based costing techniques.” Mayo Clinic Proceedings: Innovations, Quality & Outcomes 1, no. 3 (2017): 234-241. https://doi.org/10.1016/j.mayocpiqo.2017.10.002.
French, K.E. et al. “Value based care and bundled payments: Anesthesia care costs for outpatient oncology surgery using time-driven activity-based costing.” Healthcare (Amsterdam, Netherlands) 4, no. 3 (2016): 173-180. https://doi.org/10.1016/j.hjdsi.2015.08.007.
Govaert, J.A. et al. “Nationwide outcomes measurement in colorectal cancer surgery: Improving quality and reducing costs.” Journal of American College of Surgeons 222, no. 1 (2016): 19-29. https://doi.org/10.1016/j.jamcollsurg.2015.09.020.
Yun, B.J. et al. “Time-driven activity-based costing in emergency medicine.” Annals of Emergency Medicine 67, no. 6 (2016): 765-772. https://doi.org/10.1016/j.annemergmed.2015.08.004.
McLaughlin, N. et al. “Time-driven activity-based costing: A driver for provider engagement in costing activities and redesign initiatives.” Neurosurgical Focus 37, no. 5 (2014):1-9. https://doi.org/10.3171/2014.8.FOCUS14381.
Ozyurek, H., and Dinc, Y. “Time-driven Activity-based Costing.” International Journal of Business and Management Studies 6 no. 1 (2014): 97-117.
Siguenza-Guzman, L.; Alexandra, V.A.; and Cattrysse, D. “Time driven activity based costing systems for cataloguing processes: A case study.” Liber Quarterly 23, no. 3 (2014): 160–186. https://doi.org/10.18352/lq.8558.
Siguenza-Guzman, L. et al. “Using time-driven activity-based costing to support library management decisions: A case study for lending and returning processes.” The Library Quarterly 84, no. 1 (2014): 76-98. https://doi.org/10.1086/674032.
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