Algorithmic Reason

Are algorithms ruling the world today? Is artificial intelligence making life-and-death decisions? Are social media companies able to manipulate elections? As we are confronted with public and academic anxieties about unprecedented changes, this book offers a different analytical prism to investigate these transformations as more mundane and fraught. Aradau and Blanke develop conceptual and methodological tools to understand how algorithmic operations shape the government of self and other. While disperse and messy, these operations are held together by an ascendant algorithmic reason. Through a global perspective on algorithmic operations, the book helps us understand how algorithmic reason redraws boundaries and reconfigures differences. The book explores the emergence of algorithmic reason through rationalities, materializations, and interventions. It traces how algorithmic rationalities of decomposition, recomposition, and partitioning are materialized in the construction of dangerous others, the power of platforms, and the production of economic value. The book shows how political interventions to make algorithms governable encounter friction, refusal, and resistance. The theoretical perspective on algorithmic reason is developed through qualitative and digital methods to investigate scenes and controversies that range from mass surveillance and the Cambridge Analytica scandal in the UK to predictive policing in the US, and from the use of facial recognition in China and drone targeting in Pakistan to the regulation of hate speech in Germany. Algorithmic Reason offers an alternative to dystopia and despair through a transdisciplinary approach made possible by the authors’ backgrounds, which span the humanities, social sciences, and computer sciences

Risk management in international container logistics operations: risk analysis and mitigating strategies

Purpose: The aim of this thesis is to investigate risk management strategies for international logistics operations that can minimise the occurrence and/or the impact of risks in order to achieve a desirable logistics network. For this purpose, international logistics risks were analysed to find out critical risk areas, and then strategies to mitigate those risks were developed and validated in relation to organisational orientations and outcomes. Methodology: Risk identification, risk clustering and risk analysis were conducted by using focus group research and Interpretive Structural Modelling (ISM) to investigate risk areas that should be mitigated. A risk management strategy model was developed using Information Processing Theory, a review of extant supply chain risk management studies and interviews with logistics practitioners. The model was empirically tested with questionnaire survey data using descriptive statistics, ANOVA and Partial Least Square Structural Equation Modelling (PLS-SEM). Findings: International logistics risks consists of value streams; information and relationships; logistics activities; and the external environments. Among these, information and relationships risks were found to generate self-enhancing risk loops, thereby creating subsequent risk impacts after disruptions. To mitigate these risks, firms involved in international logistics implemented strategies, such as building a stable logistics network, leveraging logistics information, leveraging outsourcing contracts and developing logistics collaboration, although the level of implementation depends on the business context. Among the four strategies, building a stable logistics network and developing logistics collaboration strategies were most effective in strengthening both robustness and resilience in the logistics network. Customer orientation had positive impacts on all four strategies, but disruption orientation and quality orientation influenced certain types of strategies. Research Implications: This is the first study which has applied a three-phase risk management process to international logistics operations, thereby highlighting distinctive features of international logistics risks. This thesis empirically develops and validates a risk management strategy model which embraces both strategies and relevant tactical/operational initiatives. The antecedents and outcomes of risk management strategies were also investigated and conceptualised for future research. Practical Implications: The profile of risks, risk sources, loss types and risk levels provide a guideline for logistics managers to anticipate and proactively deal with potential risks. Also, they can evaluate the current status of risk management efforts and can benchmark suggested strategies and practices in consideration of the strategic fit to their organisations