(Re)-discovering simulation as a critical element of OM/SCM research: call for research
本文呼吁重新重视计算机模拟在运营与供应链管理研究中的作用，指出模拟能处理不确定性、动态现象和可持续性等挑战，并提供了四种有前景的模拟研究类型。
Purpose This study focuses on (re-)introducing computer simulation as a part of the research paradigm. Simulation is a widely applied research method in supply chain and operations management. However, leading journals, such as the International Journal of Operations and Production Management , have often been reluctant to accept simulation studies. This study provides guidelines on how to conduct simulation research that advances theory, is relevant, and matters. Design/methodology/approach This study pooled the viewpoints of the editorial team of the International Journal of Operations and Production Management and authors of simulation studies. The authors debated their views and outlined why simulation is important and what a compelling simulation should look like. Findings There is an increasing importance of considering uncertainty, an increasing interest in dynamic phenomena, such as the transient response(s) to disruptions, and an increasing need to consider complementary outcomes, such as sustainability, which many researchers believe can be tackled by big data and modern analytical tools. But building, elaborating, and testing theory by purposeful experimentation is the strength of computer simulation. The authors therefore argue that simulation should play an important role in supply chain and operations management research, but for this, it also has to evolve away from simply generating and analyzing data. Four types of simulation research with much promise are outlined: empirical grounded simulation, simulation that establishes causality, simulation that supplements machine learning, artificial intelligence and analytics and simulation for sensitive environments. Originality/value This study identifies reasons why simulation is important for understanding and responding to today's business and societal challenges, it provides some guidance on how to design good simulation studies in this context and it links simulation to empirical research and theory going beyond multimethod studies.