Managing risk in operations : a multi-level study

Doctoral thesis English OPEN
Ritchie, Ross Andrew
  • Subject: HD61

This research explores the management of risk in operations. It explores the different structures influencing the treatment of risk and the influence on managerial risk taking behaviours. There is limited understanding within the extant literature of the different treatment strategies for risk in operations and what influences selection of treatment strategy. This research employs an abductive approach iterating between the theoretical and empirical. There are four levels of analysis: the firm, the function, the group and the individual. The research was conducted in two European Energy companies. The research found that there is a complex interaction between organizational structures and individual perceptions in managing risk. Corporate risk structures have limited influence on the selection of risk treatments. The specification of business function (service or asset focus) informs the process of risk management and use of systems. Use of systems and valuation techniques underpin the risk prioritization process and specifically the assessment of risk. There is an order of decision influences that reflects the Levers of Control (Simons, 1995; 1998): Risk treatments are prohibited by boundary systems. Secondly, individual’s beliefs influence positive selection of treatment, and third where a treatment has not been selected through beliefs, the performance system is consulted. The performance system is most likely to influence selection of risk acceptance or risk mitigation. It is found that classification of risk has more than a semantic influence on perception and risk treatment; it can prohibit uses of certain treatments and inform priority. Understanding of the decision process matures and increases in complexity in senior managers. It is found that the performance system has influences on manager’s beliefs and in the long term, reflecting vision and mission the implementation of boundary conditions.
  • References (16)
    16 references, page 1 of 2

    2003. Accident Epidemiology and the US Chemical Industry: Accident History and WorstCase Data from RMP Info. Risk Analysis, 23, 865-881.

    KLEINDORFER, P. R. & SAAD, G. H. 2005. Managing Disruption Risks in Supply Chains.

    Production and Operations Management, 14, 53-68.

    KLEINDORFER, P. R. & WU, D. 2003. Integrating long-and short-term contracting via business-to-business exchanges for capital-intensive industries. Management Science, 49, 1597-1615.

    KLOOT, L. & MARTIN, J. 2000. Strategic performance management: A balanced approach to performance management issues in local government. Management Accounting Research, 11, 231-251.

    KNEMEYER, A. M., ZINN, W. & EROGLU, C. 2009. Proactive planning for catastrophic events in supply chains. Journal of Operations Management, 27, 141-153.

    KNIGHT, F. H. 1921. Risk, Uncertainty and Profit, London, The London School of Economics and Political Science.

    KOTZE, A. V. & HOLLOWAY, A. 1996. Reducing risk: participatory learning activities for disaster mitigation in Southern Africa, Oxfam Publications Department.

    KOVÁCS, G. & SPENS, K. M. 2005. Abductive reasoning in logistics research. International Journal of Physical Distribution & Logistics Management, 35, 132-144.

    KULKARNI, S. S., MAGAZINE, M. J. & RATURI, A. 2004. Risk Pooling Advantages of Manufacturing Network Configuration. Production and Operations Management, 13, 186- 199.

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