The distribution of value in the mobile phone supply chain

The supply chains of the mobile phone industry span national and firm boundaries. To analyze how value is distributed among the participants, a framework based on theories of firm strategy is applied, and a novel methodology is used to measure value capture in three phone models introduced from 2004 to 2008. The research shows that carriers capture the greatest value (in terms of gross profit) from each handset, followed closely by handset makers, with suppliers a distant third. However, the situation is reversed in terms of operating profit. Carriers shoulder the burden of network installation, maintenance, and upgrading, which absorbs much of the value from their subscription fees. Handset maker nationality, which may also influence supplier choice, is a key determinant of the geographic distribution of value capture. The results are also used to estimate the relationship of handset subsidies to carrier profits, which has been an issue of concern for antitrust authorities in several countries. The analysis shows how the framework can be used to calculate how much service charges might be inflated to cover the subsidies. © 2011 Elsevier Ltd. All rights reserved

The Evolving Role of Semiconductor Consortia in the United States and Japan

This article examines the interactions between public and private actors as cooperation in the semiconductor industry becomes increasingly international. The latest manifestations of multilateral collaboration are two consortia: I300I based in the United States and Selete based in Japan. Through an analysis of their structures and their origins, this article provides a deeper understanding of the complexities facing industry-wide consortia, the role of the government in promoting or inhibiting cooperation, and the lingering rivalries that impede truly global cooperation in a dynamic, high-technology industry

Semiconductor Capabilities in the U.S. and Industrializing Asia

The semiconductor industry has a rich experience with the offshoring of manufacturing and design activities. Because meaningful data about the extent of the offshoring are limited, we rely on a more qualitative analysis for our key points. We have conducted dozens of interviews with engineers and managers at numerous semiconductor and related companies in the United States, Asia, and Europe since the early 1990s. Our research also incorporates the publicly-available information in trade journals and company reports. The paper begins in section one with a brief description of the stages of semiconductor production and our analytical framework. Section two summarizes the offshoring of activities by the industry. Section three provides a more detailed discussion of the offshoring of design. Section four compares engineer capabilities in the relevant countries of Asia, where most offshoring occurs. Section five profiles the chip industry in Taiwan, China, and India. And Section six concludes with an outlook for the chip industry in the investing and host countries

Offshoring in the Semiconductor Industry: A Historical Perspective

Semiconductor design is one of the many white-collar job categories considered to be at risk from offshoring by U.S. companies via investments and outsourcing. Data about this activity are scarce and hard to interpret, but there is much to be learned from looking at earlier periods in the industry’s history when other phases of the semiconductor value chain – assembly and fabrication – experienced rapid offshore expansion. This paper reviews the lessons from these earlier offshore movements of semiconductor industry jobs in assembly. Then it analyzes the offshoring of semiconductor fabrication and then design; this analysis is based on our ongoing field research combined with trade press reports and government data. The experience of assembly and fabrication supports the claim by some that offshoring is a reasonable response to the competitive challenges and opportunities facing the semiconductor industry, and that the industry will adapt in ways that aren’t necessarily clear from the outset. Nevertheless, the outcome of the current offshoring of design provides evidence that some U.S. chip design engineers face at least short-term displacement as a result of the industry’s current round of globalization

Improving the reliability of network metrics in structural brain networks by integrating different network weighting strategies into a single graph

Structural brain networks estimated from diffusion MRI (dMRI) via tractography have been widely studied in healthy controls and in patients with neurological and psychiatric diseases. However, few studies have addressed the reliability of derived network metrics both node-specific and network-wide. Different network weighting strategies (NWS) can be adopted to weight the strength of connection between two nodes yielding structural brain networks that are almost full-weighted. Here, we scanned 5 healthy participants 5 times each, using a diffusion-weighted MRI protocol and computed edges between 90 regions of interest (ROIs) from the AAL template. The edges were weighted according to nine different methods.We propose a linear combination of these nine NWS into a single graph using an appropriate diffusion distance metric. We refer to the resulting weighted graph as an integrated weighted structural brain network (ISWBN). Additionally, we consider a topological filtering scheme that maximizes the information flow in the brain network under the constraint of the overall cost of the surviving connections. We compared each of the nine NWS and the ISWBN based on the improvement of : a) intra-class correlation coefficient (ICC) of well-known network metrics, both node-wise and per network level; and b) the recognition accuracy of each subject over the rest of the cohort, as an attempt to access the uniqueness of the structural brain network for each subject; after first applying our proposed topological filtering scheme. Based on a threshold that the network-level ICC should be > 0.90, our findings revealed six out of nine NWS lead to unreliable results at the network-level, while all nine NWS were unreliable at the node-level. In comparison, our proposed ISWBN performed as well as the best-performing individual NWS at the network-level, and the ICC was higher compared to all individual NWS at the node-level. Importantly, both network- and node-wise ICCs of network metrics derived from the topologically filtered ISBWN(ISWBNTF), were further improved compared to non-filtered ISWBN. Finally, in the recognition accuracy tests, we assigned each single ISWBNTF to the correct subject. Overall, these findings suggest that the proposed methodology results in improved characterisation of genuine between-subject differences in connectivit

Who Profits from Innovation in Global Value Chains? A Study of the iPod and Notebook PCs

In an era when new ideas are brought to the market by global value networks of specialists rather than by one company, a key question is who captures the most value from innovation in such a structure, and why? This paper addresses the question of who benefits from innovation in global value chains by looking at specific computer and electronics products. We apply a novel industry studies methodology for measuring the distribution of financial value across the supply chains for two models from Apple’s iPod family and notebook PC models from Lenovo and Hewlett-Packard (HP). These are all examples of globally innovated products, combining technologies from the U.S., Japan, and other countries, and assembled in China. Our analysis shows that the gross margins of Apple for its high-end iPod products are generally higher than those earned by HP and Lenovo for notebook PCs, although not so high as to be considered “supernormal.” A key reason for the difference is that Apple’s control of the core software, proprietary standards and complementary infrastructure of the iPod enables it to retain greater profits, whereas a large share of the PC industry profits are siphoned off to Microsoft and Intel who control key technical standards. Consistent with Teece (1986), our results confirm the importance of stages of technical evolution, appropriability regimes and complementary assets as determinants of profiting from innovation. On the other hand we find that manufacturing has become commoditized and is no longer a key to profiting from innovation in final electronic products. Also, contrary to recent suggestions in the literature, we find no evidence of a causal link between product and industry architectures. Instead, there is a vast electronics “industry architecture” that can easily support product-level value chain configurations ranging from modular to integrated

Dissecting the neurocomputational bases of patch-switching

The survival and well-being of humans require solving the patch-switching problem: we must decide when to stop collecting rewards in a current patch and travel somewhere else where gains may be higher. Previous studies suggested that frontal regions are underpinned by several processes in the context of foraging decisions such as tracking task difficulty, and/or the value of exploring the environment. To dissociate between these processes, participants completed an fMRI patch-switching learning task inspired by behavioral ecology. By analyzing >11,000 trials collected across 21 participants, we found that the activation in the cingulate cortex was closely related to several patch-switching-related variables including the decision to leave the current patch, the encounter of a new patch, the harvest value, and the relative forage value. Learning-induced changes in the patch-switching threshold were tracked by activity within frontoparietal regions including the superior frontal gyrus and angular gyrus. Our findings suggest that frontoparietal regions shape patch-switching learning apart from encoding classical non-learning foraging processes. These findings provide a novel neurobiological understanding of how learning emerges neurocomputationally shaping patch-switching behavior with implications in real-life choices such as job selection and pave the way for future studies to probe the causal role of these neurobiological mechanisms

Multimodal brain imaging reveals structural differences in Alzheimer's disease polygenic risk carriers: A study in healthy young adults

Background Recent genome-wide association studies have identified genetic loci that jointly make a considerable contribution to risk of developing Alzheimer’s disease (AD). Because neuropathological features of AD can be present several decades before disease onset, we investigated whether effects of polygenic risk are detectable by neuroimaging in young adults. We hypothesized that higher polygenic risk scores (PRSs) for AD would be associated with reduced volume of the hippocampus and other limbic and paralimbic areas. We further hypothesized that AD PRSs would affect the microstructure of fiber tracts connecting the hippocampus with other brain areas. Methods We analyzed the association between AD PRSs and brain imaging parameters using T1-weighted structural (n = 272) and diffusion-weighted scans (n = 197). Results We found a significant association between AD PRSs and left hippocampal volume, with higher risk associated with lower left hippocampal volume (p = .001). This effect remained when the APOE gene was excluded (p = .031), suggesting that the relationship between hippocampal volume and AD is the result of multiple genetic factors and not exclusively variability in the APOE gene. The diffusion tensor imaging analysis revealed that fractional anisotropy of the right cingulum was inversely correlated with AD PRSs (p = .009). We thus show that polygenic effects of AD risk variants on brain structure can already be detected in young adults. Conclusions This finding paves the way for further investigation of the effects of AD risk variants and may become useful for efforts to combine genotypic and phenotypic data for risk prediction and to enrich future prevention trials of AD

Dependence of Star Formation Activity On Stellar Mass and Environment From the Redshift One LDSS-3 Emission Line Survey (ROLES)

Using the sample from the \it Redshift One LDSS3 Emission line Survey \rm (ROLES), we probe the dependence of star formation rate (SFR) and specific star formation rate (sSFR) as a function of stellar mass $M_*$ and environment as defined by local galaxy density, in the CDFS field. Our spectroscopic sample consists of 312 galaxies with $K_{AB}<24$, corresponding to stellar mass \log(M_*/M_{\sun})>8.5, and with [OII] derived star-formation rates SFR>0.3M_{\sun}/yr, at $0.889\leq z \leq 1.149$. The results have been compared directly with the Sloan Digital Sky Survey Stripe 82 sample at $0.032\leq z \leq 0.05$. For star-forming galaxies, we confirm that there is little correlation between SFR and density at $z\sim 0$. However, for the lowest mass galaxies in our $z\sim 1$ sample, those with \log(M_*/M_{\sun})<10, we find that both the median SFR and specific SFR {\it increase} significantly with increasing local density. The "downsizing" trend for low mass galaxies to be quenched progressively later in time appears to be more pronounced in moderately overdense environments. Overall we find that the evolution of star-formation in galaxies is most strongly driven by their stellar mass, with local galaxy density playing a role that becomes increasingly important for lower mass galaxies.Comment: MNRAS accepte