Tone from the Top in Risk Management: A Complementarity Perspective on How Control Systems Influence Risk Awareness

Prompted by the weaknesses of standardized risk management approaches in the aftermath of the 2008 financial crisis, scholars, regulators, and practitioners alike emphasize the importance of creating a risk-aware culture in organizations. Recent insights highlight the special role of tone from the top as crucial driver of risk awareness. In this study, we take a systems-perspective on control system design to investigate the role of tone from the top in creating risk awareness. In particular, we argue that both interactive and diagnostic use of budgets and performance measures interact with tone from the top in managing risk awareness. Our results show that interactive control strengthens the effect of tone from the top on risk awareness, while tone from the top and diagnostic control are, on average, not interrelated with regard to creating risk awareness. To shed light on the boundary conditions of the proposed interdependencies, we further investigate whether the predicted interdependencies are sensitive to the level of perceived environmental uncertainty. We find that the effect of tone from the top and interactive control becomes significantly stronger in a situation of high perceived environmental uncertainty. Most interestingly, tone from the top and diagnostic control are complements with regard to risk awareness in settings of low perceived environmental uncertainty and substitutes at high levels of perceived environmental uncertainty.Series: Department of Strategy and Innovation Working Paper Serie

Customer Concerns about Uncertainty and Willingness to Pay in Leasing Solar Power Systems

Although solar power systems are considered as one of the most promising renewable energy sources, some uncertain factors as well as the high cost could be barriers which create customer resistance. Leasing instead of purchase, as one type of product service system, could be an option to reduce consumer concern on such issues. This study focuses on consumer concerns about uncertainty and willingness to pay for leasing solar power systems. Conjoint analysis method is used to find part worth utilities and estimate gaps of willingness to pay between attribute levels, including various leasing time lengths. The results show the part worth utilities an d relative importance of four major attributes, including leasing time. Among concerns about uncertainties, government subsidy, electricity price, reliability, and rise of new generation solar power systems were found to be significantly related to the additional willingness-to-pay for a shorter leasing time. Cluster analysis is used to identify two groups standing for high and low concerns about uncertainty. People with more concerns tend to pay more for a shorter lease time

Uncertainty and sensitivity analysis of functional risk curves based on Gaussian processes

A functional risk curve gives the probability of an undesirable event as a function of the value of a critical parameter of a considered physical system. In several applicative situations, this curve is built using phenomenological numerical models which simulate complex physical phenomena. To avoid cpu-time expensive numerical models, we propose to use Gaussian process regression to build functional risk curves. An algorithm is given to provide confidence bounds due to this approximation. Two methods of global sensitivity analysis of the models' random input parameters on the functional risk curve are also studied. In particular, the PLI sensitivity indices allow to understand the effect of misjudgment on the input parameters' probability density functions

Risk Regulation and the Faces of Uncertainty

Dr. Walker addresses the difficulty of regulators\u27 working with potentially inaccurate information and clarifies related aspects of decision making by presenting a taxonomy for the kinds of uncertainty inherent in necessarily incomplete data

Expert Elicitation for Reliable System Design

This paper reviews the role of expert judgement to support reliability assessments within the systems engineering design process. Generic design processes are described to give the context and a discussion is given about the nature of the reliability assessments required in the different systems engineering phases. It is argued that, as far as meeting reliability requirements is concerned, the whole design process is more akin to a statistical control process than to a straightforward statistical problem of assessing an unknown distribution. This leads to features of the expert judgement problem in the design context which are substantially different from those seen, for example, in risk assessment. In particular, the role of experts in problem structuring and in developing failure mitigation options is much more prominent, and there is a need to take into account the reliability potential for future mitigation measures downstream in the system life cycle. An overview is given of the stakeholders typically involved in large scale systems engineering design projects, and this is used to argue the need for methods that expose potential judgemental biases in order to generate analyses that can be said to provide rational consensus about uncertainties. Finally, a number of key points are developed with the aim of moving toward a framework that provides a holistic method for tracking reliability assessment through the design process.Comment: This paper commented in: [arXiv:0708.0285], [arXiv:0708.0287], [arXiv:0708.0288]. Rejoinder in [arXiv:0708.0293]. Published at http://dx.doi.org/10.1214/088342306000000510 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Managing the trade-off implications of global supply

The cost versus response trade-off is a growing logistics issue due to many markets being increasingly characterized by demand uncertainty and shorter product life cycles. This is exacerbated further with supply increasingly moving to low cost global sources. However, the poor response implications of global supply are often not addressed or even acknowledged when undertaking such decisions. Consequently, various practical approaches to minimising, postponing or otherwise managing the impact of the demand uncertainty are often only adopted retrospectively. Even though such generic solutions are documented through case examples we lack effective tools and concepts to support the proactive identification and resolution of such trade-offs. This paper reports on case-based theory building research, involving three cases from the UK and USA used in developing a conceptual model with associated tools, in support of such a process

A two-step fusion process for multi-criteria decision applied to natural hazards in mountains

Mountain river torrents and snow avalanches generate human and material damages with dramatic consequences. Knowledge about natural phenomenona is often lacking and expertise is required for decision and risk management purposes using multi-disciplinary quantitative or qualitative approaches. Expertise is considered as a decision process based on imperfect information coming from more or less reliable and conflicting sources. A methodology mixing the Analytic Hierarchy Process (AHP), a multi-criteria aid-decision method, and information fusion using Belief Function Theory is described. Fuzzy Sets and Possibilities theories allow to transform quantitative and qualitative criteria into a common frame of discernment for decision in Dempster-Shafer Theory (DST ) and Dezert-Smarandache Theory (DSmT) contexts. Main issues consist in basic belief assignments elicitation, conflict identification and management, fusion rule choices, results validation but also in specific needs to make a difference between importance and reliability and uncertainty in the fusion process