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"Contingency"
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Other pasts, different presents, alternative futures
\"What if there had been no World War I or no Russian Revolution? What if Napoleon had won at Waterloo in 1815, or if Martin Luther had not nailed his complaints to the church door at Wittenberg in 1517, or if the South had won the American Civil War? The questioning of apparent certainties or 'known knowns' can be fascinating and, indeed, 'What if?' books are very popular. However, this speculative approach, known as counterfactualism, has had limited impact in academic histories, historiography, and the teaching of historical methods. In this book, Jeremy Black offers a short guide to the subject, one that is designed to argue its value as a tool for public and academe alike. Black focuses on the role of counterfactualism in demonstrating the part of contingency, and thus human agency, in history, and the salutary critique the approach offers to determinist accounts of past, present, and future\"--Provided by publisher.
Book
Optimization of network redundancy and contingency planning in sustainable and resilient supply chain resource management under conditions of structural dynamics
One of the key issues in supply chain sustainability is the efficient usage of the available resources. At the same time, proactive supply chain design with disruption risk considerations frequently leads to a network redundancy which implies some resource reservations in anticipation of possible disruptions.Even if resilient supply chain design has received much attention in literature, there is a research gap in designing both resilient and sustainable supply chains. This study contributes to closing the given gap by proposing a novel methodological approach to modelling network redundancy optimization. This allows for simultaneous computation of both optimal network redundancy and proactive contingency plans, considering both supply dynamics and structural disruption risks. The novelties of this study are the integration of sustainable resource utilization and SC resilience based on coordination of structure- and flow-oriented optimization. The model uncovers a practical approach to analyze and optimize supply chain redundancy by varying processing intensities of resource consumption in the network according to supply and structural dynamics. This makes it possible to explicitly include the dynamics of resource consumption for contingency plan realization in disruption scenarios.
Journal Article
Why, where and how are organizations using blockchain in their supply chains? Motivations, application areas and contingency factors
PurposeBlockchain is increasingly being considered for applications in operations and supply chain management. However, evidence from practice is still scarce on why, where and how organizations seek to apply the technology in the supply chain across different industries. The study develops a comprehensive framework to enhance understanding of the application areas of blockchain technology in the supply chain, as well as organizations' motivations in seeking blockchain solutions and relevant contingency factors influencing applications.Design/methodology/approachThe authors investigate 50 use cases of blockchain applications in the supply chain, covering six industries. Contingency theory is applied in conducting a qualitative textual and correlation analysis to identify and compare blockchain adoption motivations, application areas and contingency factors across different industries.FindingsThe analysis develops an evidence-based framework that captures ten principal motivations in seeking blockchain solutions, three main blockchain application areas along with important application sub-categories and five clusters of contingency factors that influence blockchain deployment and its uses in different industrial sectors.Research limitations/implicationsThe study expands the limited cross-sectoral research on blockchain applications and motivations in the supply chain. Using contingency theory, it presents a comprehensive framework that captures the drivers and factors relating to blockchain adoption in the supply chain in a nomological network. The study lays the foundation for further theoretical perspectives and empirical research to investigate relevant sectoral characteristics and their importance for different types of blockchain application in the supply chain.Practical implicationsThe study informs practitioners about potential supply chain application areas that can be enhanced through blockchain technology, taking account of the specific characteristics of their products, business and manufacturing processes, supply network configurations, industry standards, regulations and market demand.Originality/valueThe study is the first to provide cross-sectoral evidence on the relevance of organizations' motivations and numerous contingency factors on blockchain application areas in the supply chain.
Journal Article
Carillion’s toll on NHS
What next for NHS trusts that depended on the liquidated contractor for construction and service provision? Nigel Hawkes reports
Journal Article
Classical tests, linear models and their extensions for the analysis of 2 × 2 contingency tables
Ecologists and evolutionary biologists are regularly tasked with the comparison of binary data across groups. There is, however, some discussion in the biostatistics literature about the best methodology for the analysis of data comprising binary explanatory and response variables forming a 2 × 2 contingency table. We assess several methodologies for the analysis of 2 × 2 contingency tables using a simulation scheme of different sample sizes with outcomes evenly or unevenly distributed between groups. Specifically, we assess the commonly recommended logistic (generalised linear model [GLM]) regression analysis, the classical Pearson chi‐squared test and four conventional alternatives (Yates' correction, Fisher's exact, exact unconditional and mid‐p), as well as the widely discouraged linear model (LM) regression. We found that both LM and GLM analyses provided unbiased estimates of the difference in proportions between groups. LM and GLM analyses also provided accurate standard errors and confidence intervals when the experimental design was balanced. When the experimental design was unbalanced, sample size was small, and one of the two groups had a probability close to 1 or 0, LM analysis could substantially over‐ or under‐represent statistical uncertainty. For null hypothesis significance testing, the performance of the chi‐squared test and LM analysis were almost identical. Across all scenarios, both had high power to detect non‐null effects and reject false positives. By contrast, the GLM analysis was underpowered when using z‐based p‐values, in particular when one of the two groups had a probability near 1 or 0. The GLM using the LRT had better power to detect non‐null results. Our simulation results suggest that, wherever a chi‐squared test would be recommended, a linear regression is a suitable alternative for the analysis of 2 × 2 contingency table data. When researchers opt for more sophisticated procedures, we provide R functions to calculate the standard error of a difference between two probabilities from a Bernoulli GLM output using the delta method. We also explore approaches to compliment GLM analysis of 2 × 2 contingency tables with credible intervals on the probability scale. These additional operations should support researchers to make valid assessments of both statistical and practical significances.
Journal Article
Managing supply chain uncertainty arising from geopolitical disruptions: evidence from the pharmaceutical industry and brexit
PurposeThis paper examines how firms of different sizes formulate and implement strategies to achieve fit with an external environment disrupted by a geopolitical event. The context of the study is the pharmaceutical industry and how it managed the supply chain uncertainty created by the United Kingdom's decision to leave the European Union, or Brexit.Design/methodology/approachData were collected longitudinally from the pro-Brexit vote on 23 June 2016, until the UK’s departure from the EU on 31 January 2020. Twenty-seven interviews were conducted in the pharmaceutical sector, including nineteen interviews with senior managers at eight case companies and eight interviews with experts working for trade associations and standards institutes. The interview findings were triangulated with Brexit policy and strategy documentation.FindingsWhen formulating strategy, multi-national enterprises (MNEs) used worst case assumptions, while large firms, and small and medium sized enterprises (SMEs) gathered knowledge as part of a “wait-and-see” strategy, allowing them to reduce perceptions of heightened supply chain uncertainty. Firms then implemented reactive and/or proactive strategies to mitigate supply chain risks.Originality/valueThe study elaborates on strategic contingency theory by identifying two important conditions for achieving strategic fit: first, companies deploy intangible resources, such as management time, to gather information and reduce perceptions of heightened supply chain uncertainty. Second, companies deploy tangible resources (supply chain redundancies, new supply chain assets) to lessen the negative outcomes of supply chain risks. Managers are provided with an empirical framework for mitigating supply chain uncertainty and risk originating from geopolitical disruptions.
Journal Article
The Tale of Cochran's Rule: My Contingency Table has so Many Expected Values Smaller than 5, What Am I to Do?
In an informal way, some dilemmas in connection with hypothesis testing in contingency tables are discussed. The body of the article concerns the numerical evaluation of Cochran's Rule about the minimum expected value in r × c contingency tables with fixed margins when testing independence with Pearson's X
2
statistic using the χ
2
distribution.
Journal Article