Upstream Volatility in the Supply Chain: The Machine Tool Industry as a Case Study

Working Draft, May 1995Cyclicality is a well known and accepted fact of life in market-driven economies. Less well known or understood, however, is the phenomenon of amplification as one looks "upstream" in the industrial supply chain. This paper discusses and explains the amplification phenomenon and its implications through the lens of one "upstream" industry that is notorious for the intensity of the business cycles it faces: the machine tool industry. Using a sparse simulation model, we have replicated much of the behavior seen in the industrial world in which machine tool companies operate. This model has allowed us to test and confirm many of our hypotheses. Two results stand out. Even though machine tool builders can do little to reduce their production volatility through choice of forecast rule, a longer view of the future leads companies to retain more of their skilled workforce. This is often cited as one of the advantages that European and Japanese companies have enjoyed: lower skilled employee turnover. The second, and most important result is that machine tool customers can do a great deal to reduce the volatility for machine tool builders through their choice of order forecast rule. Companies which use a longer horizon over which to forecast orders tend to impose less of their own volatility upon their supply base.MIT -- Leaders for Manufacturing, the International Motor Vehicle Program, the Industrial Performance Center, the International Center for Research on the Management of Technology, and the Japan Program; Chrysler, Intel, Sematech, and Texas Instruments

A note on bound entanglement and local realism

We show using a numerical approach that gives necessary and sufficient conditions for the existence of local realism, that the bound entangled state presented in Bennett et. al. Phys. Rev. Lett. 82, 5385 (1999) admits a local and realistic description. We also find the lowest possible amount of some appropriate entangled state that must be ad-mixed to the bound entangled state so that the resulting density operator has no local and realistic description and as such can be useful in quantum communication and quantum computation.Comment: 5 page

Causality - Complexity - Consistency: Can Space-Time Be Based on Logic and Computation?

The difficulty of explaining non-local correlations in a fixed causal structure sheds new light on the old debate on whether space and time are to be seen as fundamental. Refraining from assuming space-time as given a priori has a number of consequences. First, the usual definitions of randomness depend on a causal structure and turn meaningless. So motivated, we propose an intrinsic, physically motivated measure for the randomness of a string of bits: its length minus its normalized work value, a quantity we closely relate to its Kolmogorov complexity (the length of the shortest program making a universal Turing machine output this string). We test this alternative concept of randomness for the example of non-local correlations, and we end up with a reasoning that leads to similar conclusions as in, but is conceptually more direct than, the probabilistic view since only the outcomes of measurements that can actually all be carried out together are put into relation to each other. In the same context-free spirit, we connect the logical reversibility of an evolution to the second law of thermodynamics and the arrow of time. Refining this, we end up with a speculation on the emergence of a space-time structure on bit strings in terms of data-compressibility relations. Finally, we show that logical consistency, by which we replace the abandoned causality, it strictly weaker a constraint than the latter in the multi-party case.Comment: 17 pages, 16 figures, small correction

Locality and Causality in Hidden Variables Models of Quantum Theory

Motivated by Popescu's example of hidden nonlocality, we elaborate on the conjecture that quantum states that are intuitively nonlocal, i.e., entangled, do not admit a local causal hidden variables model. We exhibit quantum states which either (i) are nontrivial counterexamples to this conjecture or (ii) possess a new kind of more deeply hidden irreducible nonlocality. Moreover, we propose a nonlocality complexity classification scheme suggested by the latter possibility. Furthermore, we show that Werner's (and similar) hidden variables models can be extended to an important class of generalized observables. Finally a result of Fine on the equivalence of stochastic and deterministic hidden variables is generalized to causal models.Comment: revised version, 21 pages, submitted to Physical Review

Strategic positioning:an integrated decision process for manufacturers

Purpose – This paper describes research that has sought to create a formal and rational process that guides manufacturers through the strategic positioning decision. Design/methodology/approach – The methodology is based on a series of case studies to develop and test the decision process. Findings – A decision process that leads the practitioner through an analytical process to decide which manufacturing activities they should carryout themselves. Practical implications – Strategic positioning is concerned with choosing those production related activities that an organisations should carry out internally, and those that should be external and under the ownership and control of suppliers, partners, distributors and customers. Originality/value – This concept extends traditional decision paradigms, such as those associated with “make versus buy” and “outsourcing”, by looking at the interactions between manufacturing operations and the wider supply chain networks associated with the organisation

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Value Network Dynamics in 3G-4G Wireless Communications: a System Thinking approach to the Strategic Value Assessment Model

This article develops a map to analyze the dynamic forces that influence the structure and development of 3G (third generation) wireless communications value networks. The analysis builds on the Strategic Value Assessment Model (Fine, et al. 2002) and utilizes a qualitative System Dynamics mapping approach. The map focuses on the driving forces affecting user adoption of 3G services, focusing on customer dynamics, competitive dynamics, and technology dynamics. To analyze adoption of 3G services by customers, the articles maps the dynamics of (1) network investment and user population, (2) entry of service innovators as well as price competitors, (3) the effects of positive network externalities arising from a larger user population, (4) price compression as lower willingness-to-pay users adopt 3G services, (5) scale economies in terminal costs and prices, and (6) new content development as a draw to new users. Applying inductive systems diagrams hypotheses are integrated into a causal loop map and tested with data collected at 15 communications-industry workshops attended by 190 participants in Europe. The map aims to deepen the understanding of the possible evolutionary paths of the 3G wireless value network. The article seeks also to assess which future scenarios are plausible and what dynamic triggers might make them likely