Production
https://prod.org.br/article/doi/10.1590/0103-6513.20220020
Production
Research Article

Unveiling undergraduate production engineering students' comprehension of process flow measures

Noel Torres Júnior; Américo Lopes de Azevedo; Ana Correia Simões; Marcelo Bronzo Ladeira; Paulo Renato de Sousa; Lauro Soares de Freitas

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Abstract

Paper aims: This study analyzes the comprehension of production engineering students about the influence of some key variables on the process performance measures in a service process.

Originality: This paper points out the need for educators to re-evaluate their approaches to teaching the Operations Management (OM) principles related to process flow measures.

Research method: This study used scenario-based role-playing experiments with 2×2×2 between-subject factorial design with three independent variables (variability of activities, capacity utilization, and resource pooling) and four dependent variables related to key internal process performance measures (Flow Time, Overall Quality of service, Quality of service employees, and Queue Size). The sample was composed of 178 undergraduate production engineering students from a large university in Brazil from various institution units.

Main findings: These results show that students perceived the use of resource pooling as an impactful practice. However, the students did not correctly identify the effects of increasing resource utilization and the variability on flow time and queue size when activities are pooled.

Implications for theory and practice: The teaching of basic concepts of OM requires the support of computational tools. Undergraduate courses that contemplate subjects in the field of OM should work more intensely on simulation-based learning.

Keywords

Operations management, Process flow measures, Learning, Scenario-Based Experiment

References

Aguinis, H., & Bradley, K. J. (2014). Best practice recommendations for designing and implementing experimental vignette methodology studies. Organizational Research Methods, 17(4), 351-371. http://dx.doi.org/10.1177/1094428114547952.

Anupindi, R., Chopra, S., Deshmukh, S. D., Van Mieghem, J. A., & Zemel, E. (2011). Managing Business Process Flows: principles of operations management (3rd ed.). New Delhi: Pearson Education.

Armistead, C., & Clark, G. (1994). The “coping” capacity management strategy in services and the influence on quality performance. International Journal of Service Industry Management, 5(2), 5-22. http://dx.doi.org/10.1108/09564239410057654.

Bammert, S., König, U. M., Roeglinger, M., & Wruck, T. (2020). Exploring potentials of digital nudging for business processes. Business Process Management Journal, 26(6), 1329-1347. http://dx.doi.org/10.1108/BPMJ-07-2019-0281.

Berends, P., & Romme, G. (1999). Simulation as a research tool in management studies. European Management Journal, 17(6), 576-583. http://dx.doi.org/10.1016/S0263-2373(99)00048-1.

Brandon‐Jones, A., Piercy, N., & Slack, N. (2012). Bringing teaching to life. International Journal of Operations & Production Management, 32(12), 1369-1374. http://dx.doi.org/10.1108/01443571211284142.

Cachon, G. G., & Terwiesch, C. (2013). Matching supply with demand : an introduction to operations management (3rd ed.). New York: McGraw Hill.

Cattani, K., & Schmidt, G. M. (2005). The pooling principle. INFORMS Transactions on Education, 5(2), 17-24. http://dx.doi.org/10.1287/ited.5.2.17.

Chase, R. B. (1978). Where does the customer fit in a service operation? Harvard Business Review, 56(6), 137-142. PMid:10239167.

Christensen, L. B., Johnson, R. B., & Turner, L. A. (2015). Research methods, design, and analysis (12th ed.). Harlow: Pearson Education.

Cozby, P. C., & Bates, S. C. (2011). Methods in behavioral research (11th ed.). New York: McGraw Hill.

Dabholkar, P. A. (1994). Incorporating choice into an attitudinal framework: analyzing models of mental comparison processes. The Journal of Consumer Research, 21(1), 100. http://dx.doi.org/10.1086/209385.

De Pourcq, K., Verleye, K., Larivière, B., Trybou, J., & Gemmel, P. (2021). Implications of customer participation in outsourcing non-core services to third parties. Journal of Service Management, 32(3), 438-458. http://dx.doi.org/10.1108/JOSM-09-2019-0295.

Eckerd, S. (2016). Experiments in purchasing and supply management research. Journal of Purchasing and Supply Management, 22(4), 258-261. http://dx.doi.org/10.1016/j.pursup.2016.08.002.

Ferdows, K., & Thurnheer, F. (2011). Building factory fitness. International Journal of Operations & Production Management, 31(9), 916-934. http://dx.doi.org/10.1108/01443571111165820.

Field, J. M., Victorino, L., Buell, R. W., Dixon, M. J., Meyer Goldstein, S., Menor, L. J., Pullman, M. E., Roth, A. V., Secchi, E., & Zhang, J. J. (2018). Service operations: what’s next? Journal of Service Management, 29(1), 55-97. http://dx.doi.org/10.1108/JOSM-08-2017-0191.

Gall, M., & Rinderle-Ma, S. (2020). Assessing process attribute visualization and interaction approaches based on a controlled experiment. International Journal of Cooperative Information Systems, 29(04), 2050007. http://dx.doi.org/10.1142/S0218843020500070.

Gibbs, G., Gregory, R., & Moore, I. (1997). Teaching more students: 7-labs and practicals with more students and fewer resources. Oxford: Oxford Centre for Staff Development.

Gryna, F. M. (2004). Work overload! Redesigning jobs to minimize stress and burnout. Wisconsin: ASQ Quality Press.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2016). Multivariate data analysis (7th ed.). Harlow: Pearson Education.

Heineke, J., & Davis, M. M. (2007). The emergence of service operations management as an academic discipline. Journal of Operations Management, 25(2), 364-374. http://dx.doi.org/10.1016/j.jom.2006.11.003.

Hopp, W. J., & Spearman, M. L. (2008). Factory Physics (3rd ed.). Illinois: Waveland Press.

Jacobs, F. R., & Chase, R. B. (2012). Administração de operações e da cadeia de suprimentos (13th ed.). Porto Alegre: McGraw Hill Brasil.

Jasti, N. V. K., Kota, S., & Venkataraman, P. B. (2021). An impact of simulation labs on engineering students’ academic performance: a critical Investigation. Journal of Engineering Design and Technology, 19(1), 103-126. http://dx.doi.org/10.1108/JEDT-03-2020-0108.

Kandampully, J. (2000). The impact of demand fluctuation on the quality of service: A tourism industry example. Managing Service Quality, 10(1), 10-19. http://dx.doi.org/10.1108/09604520010307012.

Krajewski, L. J., Ritzman, L. P., & Malhotra, M. (2009). Administração da produção e operações (8th ed.). São Paulo: Prentice Hall Brasil.

Larreche, J.-C. (1987). On simulations in business education and research. Journal of Business Research, 15(6), 559-571. http://dx.doi.org/10.1016/0148-2963(87)90039-7.

Lemke, F., Clark, M., & Wilson, H. (2011). Customer experience quality: an exploration in business and consumer contexts using repertory grid technique. Journal of the Academy of Marketing Science, 39(6), 846-869. http://dx.doi.org/10.1007/s11747-010-0219-0.

Liker, J. K. (2021). The Toyota Way: 14 management principles from the world’s greatest manufacturer (2nd ed.). New York: McGraw-Hill Education.

Little, J. D. C. (2011). Little’s law as viewed on its 50th anniversary. Operations Research, 59(3), 536-549. http://dx.doi.org/10.1287/opre.1110.0940.

Machuca, J. D., González-Zamora, M. D. M., & Aguilar-Escobar, V. G. (2007). Service Operations Management research. Journal of Operations Management, 25(3), 585-603. http://dx.doi.org/10.1016/j.jom.2006.04.005.

Mansar, S. L., & Reijers, H. A. (2005). Best practices in business process redesign: validation of a redesign framework. Computers in Industry, 56(5), 457-471. http://dx.doi.org/10.1016/j.compind.2005.01.001.

Medina-López, C., Alfalla-Luque, R., & Arenas-Márquez, F. J. (2011). Active learning in Operations Management: interactive multimedia software for teaching JIT/Lean Production. Journal of Industrial Engineering and Management, 4(1), 31-80. http://dx.doi.org/10.3926/jiem.2011.v4n1.p31-80.

Min, B. S., & Smyth, R. (2014). Corporate governance, globalization and firm productivity. Journal of World Business, 49(3), 372-385. http://dx.doi.org/10.1016/j.jwb.2013.07.004.

Negrão, L. L. L., Godinho Filho, M., & Marodin, G. (2017). Lean practices and their effect on performance: a literature review. Production Planning and Control, 28(1), 33-56.

Oliva, R. (2001). Tradeoffs in responses to work pressure in the service industry. California Management Review, 43(4), 26-43. http://dx.doi.org/10.2307/41166099.

Poornikoo, M., & Qureshi, M. A. (2019). System dynamics modeling with fuzzy logic application to mitigate the bullwhip effect in supply chains. Journal of Modelling in Management, 14(3), 610-627. http://dx.doi.org/10.1108/JM2-04-2018-0045.

Pound, E. S., Bell, J. H., & Spearman, M. L. (2014). Factory physics for managers: how leaders improve performance in a post-lean six sigma world. New York: McGraw Hill.

Pullman, M. E., & Moore, W. L. (1999). Optimal service design: Integrating marketing and operations perspectives. International Journal of Service Industry Management, 10(2), 239-260. http://dx.doi.org/10.1108/09564239910264361.

R Core Team (2021). R: a language and environment for statistical computing. R Foundation for Statistical Computing. Retrieved in 18 Februart 2022, from https://www.R-project.org/

Reid, R. D., & Sanders, N. R. (2005). Gestão de operações. Rio de Janeiro: LTC.

Rungtusanatham, M., Wallin, C., & Eckerd, S. (2011). The vignette in a scenario-based role-playing experiment. The Journal of Supply Chain Management, 47(3), 9-16. http://dx.doi.org/10.1111/j.1745-493X.2011.03232.x.

Ryan, K. J., Joseph, V. B., Cooke, R. E., Height, D. I., Jonsen, A. R., King, P., & Lebacqz, K. (1979). The Belmont Report: ethical principles and guidelines for the protection of human subjects of research. In The National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. Washington, DC: Dhew Publication.

Salas, E., Wildman, J. L., & Piccolo, R. F. (2009). Using simulation-based training to enhance management education. Academy of Management Learning & Education, 8(4), 559-573.

Sayer, N. J., & Williams, B. (2007). Lean for dummies. Hoboken: Wiley Publishing, Inc.

Schmenner, R. W. (2012). Getting and staying productive: applying swift, even flow to practice. Cambridge: Cambridge University Press. http://dx.doi.org/10.1017/CBO9781139108775.

Shadish, W. R., & Cook, T. D. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin Company.

Showanasai, P., Lu, J., & Hallinger, P. (2013). Developing tools for research on school leadership development. Journal of Educational Administration, 51(1), 72-91. http://dx.doi.org/10.1108/09578231311291440.

Slack, N., Brandon-Jones, A., & Johnston, R. (2013a). Operations management (7th ed.). Harlow: Pearson.

Slack, N., Chambers, S., Johnston, R., & Betts, A. (2013b). Gerenciamento de operações e de processos: princípios e práticas de impacto estratégico (2ª ed.). Porto Alegre: Bookman.

Spearman, M. L., & Hopp, W. J. (2009). Teaching operations management from a science of manufacturing. Production and Operations Management, 7(2), 132-145. http://dx.doi.org/10.1111/j.1937-5956.1998.tb00445.x.

Stevenson, W. J. (2014). Operations management. England: McGraw-Hill Education.

Webster Junior, M., & Sell, J. (2014). Laboratory experiments in the social sciences (2nd ed.). London: Academic Press.

Yao, Y., Duan, Y., & Huo, J. (2021). On empirically estimating bullwhip effects: measurement, aggregation, and impact. Journal of Operations Management, 67(1), 5-30. http://dx.doi.org/10.1002/joom.1090.

Yin, X. (2021). Measuring the bullwhip effect with market competition among retailers: a simulation study. Computers & Operations Research, 132, 105341. http://dx.doi.org/10.1016/j.cor.2021.105341.
 


Submitted date:
02/18/2022

Accepted date:
08/10/2022

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