John R. Macdonald

Making sense of transient responses in simulation studies

Traditional simulation modelling focuses upon the analysis of steady-state data. This focus may not be appropriate, however, for the study of transient responses – data reflecting some form of disruption or change in the system norms. Transient responses are often encountered when dealing with new product introductions, changes in production systems, or supply chain disruptions. In these situations, it is the transient response, how the system responds to these changes as well as the tactics and strategies used to deal with these changes, that tend to be of the greatest interest. Unfortunately, current approaches that focus on analysing such responses are limited. This paper introduces a new approach for analysing transient responses – one that merges outlier detection, a time series analysis tool, with simulation modelling. This combined approach allows the researcher to identify those factors that have the greatest impact upon operations during these transient conditions. Using a simulated supply chain disruption to illustrate the potential of the approach, it is shown that the new approach expands the applicability of simulation and enables certain types of problems to be investigated with confidence not previously provided.

Stages of Supply Chain Disruption Response: Direct, Constraining, and Mediating Factors for Impact Mitigation

It is well established that supply chain disruptions can have a severe negative impact on firms and general wisdom suggests that this impact can be mitigated by quick responses. Aside from a few anecdotes, however, little is known about the decision-making process that leads to speedy responses and about its impeding and supporting antecedents. Using the organizational information-processing perspective, this empirical study unravels the disruption management process along a sequence of four stages—disruption recognition, disruption diagnosis, response development, and response implementation—and hypothesizes constraining and mediating effects of these stages. The findings contribute to an improved understanding of the role that the decision stages play in mitigating supply chain disruptions, and confirm the prediction that the speed with which information is processed and the stages are worked through positively affects supply chain performance. In addition, the findings suggest that one of the stages, diagnosis, acts as a constraining factor to the other stages. The stages also play a mediating role between the impact that the disruption has and a firms readiness (prior to a disruption), dependence on a key supplier, and supply chain complexity. This provides guidance to decision makers in the application of resources both prior to a negative event and during a disruption recovery.

Supply chain risk and resilience: theory building through structured experiments and simulation

The research literature of supply chain risk and resilience is at a critical developmental stage. Studies have established the importance of these topics both to researchers and practitioners. They also have identified factors contributing to risk, the impact of risk and disruptions on performance, and the strategies and tactics used to build the capacity for supply chain resilience. Although these efforts can provide support for constructing a theory of risk and resilience, researchers are currently restricted in their ability to build such a theory by the difficulty of collecting the necessary data. This paper contributes to this literature development effort by summarising prior research reviews and developing a three-component framework aimed at helping researchers to build better theories. This is accomplished through combining structured experimental design with discrete-event simulations of supply chains. The result is a methodology that allows researchers to develop better understanding of the factors that link a disruption to its impact on supply chain performance through both direct and interaction effects. Following the methodology development, the paper concludes with an example using the factors of shock interarrival time, supply chain connectivity and buffer stocks to illustrate the potential for contributing to the theory-building process.

X-SCM Network Design

1. Introduction and overview of the book, Bjorn Stensaker and Lee Harvey 2. Accountability: Understandings and challenges, Bjorn Stensaker and Lee Harvey Part I. An overview of accountability schemes in different regions 3. Accountability in Australia: More power to government and market, Jeanette Baird 4. Accountability in Africa: A disciplinary power in African higher education systems, Gerald Wangenge-Ouma & Patricio V. Langa 5. Accountability in China: Primitive attempts, Shuiyun Liu 6. Accountability in Eastern Europe: Becoming like everywhere else? Paul Temple 7. Accountability in Western Europe: Shifting quality assurance paradigms, Andree Sursock 8. Accountability in Latin America: Focusing on quality assurance and funding mechanisms, Maria-Jose Lemaitre 9. Accountability in the United States: Sorting through an American muddle, Robert Zemsky Part II. International trends, challenges and responses to accountability initiatives 10. Accountability and Cross-border Higher Education: Dynamics, trends and challenges, Robin Middlehurst 11. Transnational Accountability Initiatives: The case of the EUA-audits, Alberto Amaral and Maria Joao Rosa 12. Managerial and Political Strategies for Handling Accountability, William F. Massy 13. Conclusions and reflections, Bjorn Stensaker and Lee Harvey