Resilience markers for safer systems and organisations

If computer systems are to be designed to foster resilient performance it is important to be able to identify contributors to resilience. The emerging practice of Resilience Engineering has identified that people are still a primary source of resilience, and that the design of distributed systems should provide ways of helping people and organisations to cope with complexity. Although resilience has been identified as a desired property, researchers and practitioners do not have a clear understanding of what manifestations of resilience look like. This paper discusses some examples of strategies that people can adopt that improve the resilience of a system. Critically, analysis reveals that the generation of these strategies is only possible if the system facilitates them. As an example, this paper discusses practices, such as reflection, that are known to encourage resilient behavior in people. Reflection allows systems to better prepare for oncoming demands. We show that contributors to the practice of reflection manifest themselves at different levels of abstraction: from individual strategies to practices in, for example, control room environments. The analysis of interaction at these levels enables resilient properties of a system to be ‘seen’, so that systems can be designed to explicitly support them. We then present an analysis of resilience at an organisational level within the nuclear domain. This highlights some of the challenges facing the Resilience Engineering approach and the need for using a collective language to articulate knowledge of resilient practices across domains

Hand in the Cookie Jar: An Experimental Investigation of Equity-based Compensation and Managerial Fraud

The use of equity-based compensation is an increasingly popular means by which to align the incentives of top management with that of the shareholders. However, recent theoretical and empirical research suggests that the use of equity-based compensation has the unintended consequence of creating the incentive to commit managerial fraud of the type being reported in the press. This paper reports experimental evidence showing that the amount of fraud committed by subjects is positively correlated with the level of equity, as is the level of effort. As well, the amount of fraud that is committed is negatively correlated with the probability of detection and subjects’ risk aversion. The experimental design permits the identification of causal relations in the directions just noted. Key Words:

The Process of Innovation

The paper argues that innovation processes can be cognitive, organisational and/or economic. They happen in conditions of uncertainty and (in the capitalist system) of competition. Three broad, overlapping sub-processes of innovation are identified: the production of knowledge; the transformation of knowledge into products, systems, processes and services; and the continuous matching of the latter to market needs and demands. The paper identifies key trends in each of these areas: (1) increasing specialisation in knowledge production; (2) increasing complexity in physical artefacts, and in the knowledge bases underpinning them; and (3) the difficulties of matching technological opportunities with market needs and organisational practices. Despite advances in scientific theory and information and communication technologies (ICTs), innovation processes remain unpredictable and difficult to manage. They also vary widely according to the firm's sector and size. Only two innovation processes remain generic: co-ordinating and integrating specialised knowledge, and learning in conditions of uncertainty. The paper also touches on the key challenges now facing 'innovation managers' within modern industrial corporations, bearing in mind the highly contingent nature of innovation.innovation processes, specialised knowledge production, knowledge transformation, modern industrial corporations

Data-driven design of intelligent wireless networks: an overview and tutorial

Data science or "data-driven research" is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves

Rationality and the Foundations of Positive Political Theory

In this paper, we discuss and debunk the four most common critiques of the rational choice research program (which we prefer to call Positive Political Theory) by explaining and advocating its foundations: the rationality assumption, component analysis (abstraction), strategic behavior, and theory building, in turn. We argue that the rationality assumption and component analysis, properly understood, can be seen to underlie all social science, despite the protestations of critics. We then discuss the two ways that PPT most clearly contributes to political science (i.e., what distinguishes it from other research programs), namely the introduction of strategic behavior (people do not just act; they interact) and PPT’s more careful attention to the theory-building step within the scientific method. We explain the roles of theory- building and of empirical “testing,” respectively, in scientific inquiry, and the criteria by which theories should and should not be judged

Upper-Confidence Bound for Channel Selection in LPWA Networks with Retransmissions

In this paper, we propose and evaluate different learning strategies based on Multi-Arm Bandit (MAB) algorithms. They allow Internet of Things (IoT) devices to improve their access to the network and their autonomy, while taking into account the impact of encountered radio collisions. For that end, several heuristics employing Upper-Confident Bound (UCB) algorithms are examined, to explore the contextual information provided by the number of retransmissions. Our results show that approaches based on UCB obtain a significant improvement in terms of successful transmission probabilities. Furthermore, it also reveals that a pure UCB channel access is as efficient as more sophisticated learning strategies.Comment: The source code (MATLAB or Octave) used for the simula-tions and the figures is open-sourced under the MIT License, atBitbucket.org/scee\_ietr/ucb\_smart\_retran