Effects of Manipulation on Attributions of Causation,Free Will,and Moral Responsibility

If someone brings about an outcome without intending to, is she causally and morally responsible for it? What if she acts intentionally, but as the result of manipulation by another agent? Previous research has shown that an agent's mental states can affect attributions of causal and moral responsibility to that agent , but little is known about what effect one agent's mental states can have on attributions to another agent. In Experiment 1, we replicate findings that manipulation lowers attributions of responsibility to manipulated agents. Experiments 2–7 isolate which features of manipulation drive this effect, a crucial issue for both philosophical debates about free will and attributions of responsibility in situations involving social influence more generally. Our results suggest that “bypassing” a manipulated agent's mental states generates the greatest reduction in responsibility, and we explain our results in terms of the effects that one agent's mental states can have on the counterfactual relations between another agent and an outcome.     

Selection of a Third‐Party Logistics Provider: Capturing the Interaction and Influence of Performance Metrics with the Analytical Network Process

When a business decides to outsource its logistics operations to improve its performance, the organization will need to select a third‐party logistics provider (3PL) that shares common goals and satisfies service level requirements. In this paper, we identify a set of 3PL performance measures from the perspective of the supply chain and organize them into a time‐phased format, beginning with the post production stage and continuing through the delivery of the goods to the customer distribution center. The supply chain flow is presented as a Metrics Arrow. To integrate the performance metrics (PM) into one model, we propose an analytical network process (ANP) to capture all PM and to understand the interrelated influences among them. Additionally, to derive the weights for PM, the proposed ANP model offers managerial insight into the relative impact of each metric as well as warning signals or trigger points within the network of PM. The model provides a realistic framework to choose the 3PL that can help achieve the greatest improvements within the supply chain. Copyright © 2012 John Wiley & Sons, Ltd.