Armchair detectives and the social construction of falsehoods: an actor–network approach

ABSTRACT

This paper examines two large-scale cases ? the 2013 Boston bombing and the 2015 Bangkok bombing, each of which spurred an online investigation conducted by concerned citizens to find the bombers. While both bombing cases had different cultural discourses, the processes and outcomes of the online investigation were similar: there were rampant speculation and rumor-mongering, as well as false accusations and harassment of innocent suspects. The aim of the paper is to understand how such acts of mob justice happened. Using actor–network theory, a theoretical and methodological tool for mapping out the networks human and non-human interactions, I discuss two types of networks found in both investigations. The two network types demonstrate how a claim can be construed as fact or fiction through such networks of interaction. In light of debates on the proliferation of fake news and alternative facts, the findings have implications for the current and precarious state of truth in today’s society.     

Standard Container Size Discounts and the Single-Period Inventory Problem*

This paper analyzes the problem of choosing the optimal order quantity and its associated number of standard containers making up the order for single-period inventory models under standard container size discounts. A range is determined that contains the optimal order quantity. Two algorithms are presented. The first algorithm solves the general case in which there is no restriction on the types of containers included in an order. The second algorithm solves a more restricted policy that requires the buyer to accept the order with successively smaller container sizes.     

All-Units Discounts for Standard Container Sizes

Some vendors offer their products to a purchaser in various container sizes. Normally, vendors will offer larger all-units discounts on larger container sizes. Two algorithms have been developed in this paper to solve for the optimal number of each container size and the order quantity for the deterministic economic order quantity (EOQ) situation. The first algorithm, based in part on the dynamic programming solution to knapsack problems, solves the general case. The second algorithm, based in part on the dominance relations inherent in the pricing schedule, solves the more restricted case in which the purchaser is forced to accept the discount in the following manner. An order must be filled with containers of successively smaller sizes, beginning with the largest size. The purchaser is forced to accept the largest discount first, then the next largest, and so on.     

A Comparison of Three Joint Ordering Inventory Policies*

This paper evaluates the performance of a joint ordering inventory policy which was first suggested and characterized by Renberg and Planche [14]. This paper shows that the policy is easily characterized for Poisson demands. This policy is then compared with two other joint ordering policies—the well-known (S, c, s) or can-order policy of Balintfy [3] and the recent periodic policies suggested by Atkins and lyogun [2]. For a continuous review operating environment, the Renberg and Planche policy utilizes a group reorder point and a combined order quantity (Q), with each item maintaining an order-up-to level (S). For the can-order policy, each item in the product group has a must-order point (s), a can-order point (c) and an order-up-to level (S). The periodic policies require that item orders be grouped at some fixed scheduled intervals. Using long-run total average costs as the basis, it is shown that no one policy is superior to the others in all the examples tested. In some cases, the Renberg and Planche policy performs surprisingly well.