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Uncertainty and supply chain risk: The moderating role of supply chain flexibility in risk mitigation

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TLDR
In this paper, the authors investigate the relationship between environmental uncertainty and supply chain risk and the moderating effect of supply chain flexibility and identify appropriate types of flexibility to mitigate the three major aspects of risk: supply risk, manufacturing process risk and delivery risk.
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This article is published in International Journal of Production Economics.The article was published on 2017-11-01. It has received 237 citations till now. The article focuses on the topics: Supply chain risk management & Supply chain.

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Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience

TL;DR: The study model reconciles two different streams of literature: data analytics capability as a means to improve information-processing capacity and supply chain resilience as a Means to reduce a ripple effect in supply chain or quickly recover after disruptions in the supply chain.
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Blockchain technology for enhancing swift-trust, collaboration and resilience within a humanitarian supply chain setting

TL;DR: This study proposes a theoretical model to understand how BT can influence operational supply chain transparency (OSTC) and ST among actors engaged in disaster relief operations and shows how BT-enabled ST can further improve collaboration (CO) among actors engage in disaster Relief operations and enhance supply chain resilience (SCR).
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Supply chain risk management and operational performance: The enabling role of supply chain integration

TL;DR: In this article, a covariance-based structural equation modeling is applied to test the developed hypotheses using data of 931 manufacturing companies obtained from the sixth version of International Manufacturing Strategy Survey (IMSS VI).
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Blockchain adoption in operations and supply chain management: empirical evidence from an emerging economy

TL;DR: The adoption of technologies by the operations and supply chain management (OSCM) field is leading to extraordinary disruptions as mentioned in this paper. And with the rapid emergence of cutting-edge and more disruptive tec...
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Supply Chain Recovery Challenges in the Wake of COVID-19 Pandemic

TL;DR: In this article, a Delphi-based grey decision-making trial and evaluation laboratory (DEMATEL) methodology was used to analyze the data and identify the major supply chain recovery challenges from the impacts of the COVID-19 pandemic, the grey DEMATEL approach helped categorize the causal relationships among these challenges.
References
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Book

Statistical Power Analysis for the Behavioral Sciences

TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
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The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations.

TL;DR: This article seeks to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating the many ways in which moderators and mediators differ, and delineates the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena.
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Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
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Self-Reports in Organizational Research: Problems and Prospects

TL;DR: In this paper, the authors identify six categories of self-reports and discuss such problems as common method variance, the consistency motif, and social desirability, as well as statistical and post hoc remedies and some procedural methods for dealing with artifactual bias.
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PLS-SEM: Indeed a Silver Bullet

TL;DR: The authors conclude that PLS-SEM path modeling, if appropriately applied, is indeed a "silver bullet" for estimating causal models in many theoretical models and empirical data situations.
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