Purpose The purpose of this paper is to present a conceptual framework on resilience types in supply chain networks. Design/methodology/approach Using a complex adaptive systems perspective as an organizing framework, the paper explores three forms of resilience: engineering, ecological and evolutionary and their antecedents and links these to four phases of supply chain resilience (SCRES): readiness, response, recovery, growth and renewal. Findings Resilient supply chains need all three forms of resilience. Efficiency and system optimization approaches may promote quick recovery after a disruption. However, system-level response requires adaptive capabilities and transformational behaviors may be needed to move supply chains to new fitness levels after a disruption. The three resilience types discussed are not mutually exclusive, but rather complement each other and there are synergies and tradeoffs among these resilience types. Research limitations/implications The empirical validation of the theoretical propositions will open up new vistas for supply chain research. Possibilities exist for analyzing and assessing SCRES in multiple and more comprehensive ways. Practical implications The findings of the research can help managers refine their approaches to managing supply chain networks. A more balanced approach to supply chain management can reduce the risks and vulnerabilities associated with supply chain disruptions. Originality/value This study is unique as it conceptualizes SCRES in multiple ways, thereby extending our understanding of supply chain stability.

Purpose -The overall purpose of this research is to increase understanding of the factors that promote the effective use of simulations in management education. Design/methodology/approach -This study uses data from 49 teams of respondents performing a management simulation exercise to achieve the research purpose. Respondents took part in the simulation in teams and were required to manage a business in the global athletic industry. Respondents completed a 21-item instrument designed to assess individual learning. Learning was factor-analyzed and three factors derived that correspond to problem-solving skills, teamwork and seeing oneself as a manager. Measures were developed to assess team dynamic factors (emotional and task conflict), the user-friendliness and realism of the simulation. Findings -The study showed that the nature of the simulation and team dynamics affected learning and performance. First, the extent to which users perceived the simulation as reflective of real life situations was positively associated with learning. Second, the ease of use of the simulation positively affected learning. Third, emotional conflict in the team was negatively associated with learning. Fourth, task conflict, measured by the degree of exchange of ideas, was positively associated with learning. Finally, the ease of use and task conflict in a team positively affected team performance, while emotional conflict had a negative relationship to team performance.Research limitations/implications -The research had some limitations. Reliance was placed on cross-sectional data and a snapshot measure taken of performance and learning. In addition, respondents had fairly limited work experience and that may affect their perception of the simulation. This research can be extended by testing the model with managers with substantial years of experience. Including the role of game administrators may also yield greater insight. Practical implications -The study demonstrated that carefully choosing simulations could affect their effectiveness. The user-friendliness and realism of the simulation are two important criteria. In addition, the findings indicate that those administering simulations with teams should pay attention to team dynamics. The findings also suggest that factors that affect individual learning may not necessarily affect performance on the simulation. This implies that game administrators need to define their objectives clearly. Originality/value -This study has increased understanding of the factors that determine the effectiveness of management simulations. The present research bridged some of the gaps in one's understanding by proposing and empirically testing factors that may lead to the identification of suitable management simulations. It also increased understanding of the situational dynamics that enhance the effective use of simulations. This study, as far is known, is the first to separate learning and performance as outcomes.

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PurposeThe purpose of this paper is to develop a conceptual framework for extending an understanding of resilience in complex adaptive system (CAS) such as supply chains using the adaptive cycle framework. The adaptive cycle framework may help explain change and the long term dynamics and resilience in supply chain networks. Adaptive cycles assume that dynamic systems such as supply chain networks go through stages of growth, development, collapse and reorientation. Adaptive cycles suggest that the resilience of a complex adaptive system such as supply chains are not fixed but expand and contract over time and resilience requires such systems to navigate each of the cycles’ four stages successfully.Design/methodology/approachThis research uses the adaptive cycle framework to explain supply chain resilience (SCRES). It explores the phases of the adaptive cycle, its pathologies and key properties and links these to competences and behaviors that are important for system and SCRES. The study develops a conceptual framework linking adaptive cycles to SCRES. The goal is to extend dynamic theories of SCRES by borrowing from the adaptive cycle framework. We review the literature on the adaptive cycle framework, its properties and link these to SCRES.FindingsThe key insight is that the adaptive cycle concept can broaden our understanding of SCRES beyond focal scales, including cross-scale resilience. As a framework, the adaptive cycle can explain the mechanisms that support or prevent resilience in supply chains. Adaptive cycles may also give us new insights into the sort of competences required to avoid stagnation, promote system renewal as resilience expands and contracts over time.Research limitations/implicationsThe adaptive cycle may move our discussion of resilience beyond engineering and ecological resilience to include evolutionary resilience. While the first two presently dominates our theorizing on SCRES, evolutionary resilience may be more insightful than both are. Adaptive cycles capture the idea of change, adaptation and transformation and allow us to explore cross-scale resilience.Practical implicationsKnowing how to prepare for and overcoming key pathologies associated with each stage of the adaptive cycle can broaden our repertoire of strategies for managing SCRES across time. Human agency is important for preventing systems from crossing critical thresholds into imminent collapse. More importantly, disruptions may present an opportunity for innovation and renewal for building more resilience supply chains.Originality/valueThis research is one of the few studies that have applied the adaptive cycle concept to SCRES and extends our understanding of the dynamic structure of SCRES

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