Understanding supply chain disruption risk with the aid of social networks and information flows analysis

Supply Chain Risk Management (SCRM) has become a popular area of research and study in recent years. This can be highlighted by the number of peer reviewed articles that have appeared in academic literature. This coupled with the realisation by companies that SCRM strategies are required to mitigate the risks that they face, makes for challenging research questions in the field of risk management. The challenge that companies face today is not only to identify the types of risks that they face, but also to assess the indicators of risk that face them. This will allow them to mitigate that risk before any disruption to the supply chain occurs. The use of social network theory can aid in the identification of disruption risk. This thesis proposes the combination of social networks, behavioural risk indicators and information management, to uniquely identify disruption risk. The propositions that were developed from the literature review and exploratory case study in the aerospace OEM, in this thesis are:- By improving information flows, through the use of social networks, we can identify supply chain disruption risk. - The management of information to identify supply chain disruption risk can be explored using push and pull concepts. The propositions were further explored through four focus group sessions, two within the OEM and two within an academic setting. The literature review conducted by the researcher did not find any studies that have evaluated supply chain disruption risk management in terms of social network analysis or information management studies. The evaluation of SCRM using these methods is thought to be a unique way of understanding the issues in SCRM that practitioners face today in the aerospace industry.

Investigating the supply and demand relationship in a profession: the English and Welsh schools of librarianship and information Studies and the Higher Education Library and Information Services employment sector in England and Wales.

Concern has been expressed in the professional literature - borne out by professional experience and observation - that the supply and demand relationship existing between the 13 English and Welsh Library and Information Studies (LIS) Schools (as providers of `First Professional' staff) and the Higher Education Library and Information Services (HE LIS) sector of England and Wales (as one group of employers of such staff) is unsatisfactory and needs attention. An appropriate methodology to investigate this problem was devised. A basic content analysis of Schools' curricular and recruitment material intended for public consumption was undertaken to establish an overview of the LIS initial professional education system in England and Wales, and to identify and analyse any covert messages imparted to readers. This was followed by a mix of Main Questionnaires and Semi-Structured Interviews with appropriate populations. The investigation revealed some serious areas of dissatisfaction by the HE LIS Chiefs with the role and function of the Schools. Considerable divergence of views emerged on the state of the working relationships between the two sectors and on the Schools' successes in meeting the needs of the HE LIS sector and on CPD provision. There were, however, areas of substantial and consistent agreement between the two sectors. The main implications of the findings were that those areas encompassing divergence of views were worrying and needed addressing by both sides. Possible ways forward included recommendations on improving the image of the profession purveyed by the Schools; the forming of closer and more effective inter-sectoral relationships; recognising fully the importance of `practicum' and increasing and sustaining the network of `practicum' providers.

Combining temporal and spectral information with spatial mapping to identify differences between phonological and semantic networks:a magnetoencephalographic approach

Early, lesion-based models of language processing suggested that semantic and phonological processes are associated with distinct temporal and parietal regions respectively, with frontal areas more indirectly involved. Contemporary spatial brain mapping techniques have not supported such clear-cut segregation, with strong evidence of activation in left temporal areas by both processes and disputed evidence of involvement of frontal areas in both processes. We suggest that combining spatial information with temporal and spectral data may allow a closer scrutiny of the differential involvement of closely overlapping cortical areas in language processing. Using beamforming techniques to analyze magnetoencephalography data, we localized the neuronal substrates underlying primed responses to nouns requiring either phonological or semantic processing, and examined the associated measures of time and frequency in those areas where activation was common to both tasks. Power changes in the beta (14-30 Hz) and gamma (30-50 Hz) frequency bandswere analyzed in pre-selected time windows of 350-550 and 500-700ms In left temporal regions, both tasks elicited power changes in the same time window (350-550 ms), but with different spectral characteristics, low beta (14-20 Hz) for the phonological task and high beta (20-30 Hz) for the semantic task. In frontal areas (BA10), both tasks elicited power changes in the gamma band (30-50 Hz), but in different time windows, 500-700ms for the phonological task and 350-550ms for the semantic task. In the left inferior parietal area (BA40), both tasks elicited changes in the 20-30 Hz beta frequency band but in different time windows, 350-550ms for the phonological task and 500-700ms for the semantic task. Our findings suggest that, where spatial measures may indicate overlapping areas of involvement, additional beamforming techniques can demonstrate differential activation in time and frequency domains. © 2012 McNab, Hillebrand, Swithenby and Rippon.

The relationship between market share and information in a high-tech industry

The role of information in high-technology markets is critical (Dutta, Narasimhan and Rajiv 1999; Farrell and Saloner 1986; Weiss and Heide 1993). In these markets, the volatility and volume of information present managers and researchers with the considerable challenge of monitoring such information and examining how potential customers may respond to it. This article examines the effects of the type and volume of information on the market share of different technological standards in the Local Area Networks (LAN) industry. We identify three different types of information: technological, availability and adoption. Our empirical application suggests that all three types of information have significant effects on the market share of a technological standard, but their direction and magnitude differ. More specifically, technology-related information is negatively related to market share as it demonstrates that the underlying technology is immature and still evolving. Both availability and adoption-related information have a positive effect on market share, but the former is larger than the latter. We conclude that high-tech firms should emphasize the dissemination of information, especially availability-related, as part of their promotional strategy for a new technology. Otherwise, they may risk missing an opportunity to achieve a higher share and establish their market presence.

Finding structures in information networks using the affinity network

This thesis proposes a novel graphical model for inference called the Affinity Network,which displays the closeness between pairs of variables and is an alternative to Bayesian Networks and Dependency Networks. The Affinity Network shares some similarities with Bayesian Networks and Dependency Networks but avoids their heuristic and stochastic graph construction algorithms by using a message passing scheme. A comparison with the above two instances of graphical models is given for sparse discrete and continuous medical data and data taken from the UCI machine learning repository. The experimental study reveals that the Affinity Network graphs tend to be more accurate on the basis of an exhaustive search with the small datasets. Moreover, the graph construction algorithm is faster than the other two methods with huge datasets. The Affinity Network is also applied to data produced by a synchronised system. A detailed analysis and numerical investigation into this dynamical system is provided and it is shown that the Affinity Network can be used to characterise its emergent behaviour even in the presence of noise.

Innovation and policy networks:the social shaping of BSE-related technologies and the inadequate assessmant of related risks

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR CONSULTATION

Combining deformable templates and neural networks for HCR

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The development of a computer simulation model of the interaction between the supply and usage of major components in car assembly you use in stock control

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Competence requirements for managing supply in interorganizational networks

The authors address the growing call for research into the management of supply networks serving the public sector. Building on prior action research, this empirical paper focuses on the management of supply in interorganizational, health sector networks identifying the competence requirements (skills, knowledge, traits, and behavioural indicators) associated with effective team performance. Drawing on empirical data, the authors present a competence framework that aims to capture a team’s tacit understanding of strategic supply management. Competence indicators are organized into six themes: network understanding; developing network position; relationship management; learning, knowledge and knowledge management; strategy formulation; strategy implementation. Finally, the relevance of the framework to boundary spanning personnel outside the purchasing function and to other organizations is considered.

Dialogue, partnership and empowerment for network and information security:the changing role of the private sector from objects of regulation to regulation shapers

The protection of cyberspace has become one of the highest security priorities of governments worldwide. The EU is not an exception in this context, given its rapidly developing cyber security policy. Since the 1990s, we could observe the creation of three broad areas of policy interest: cyber-crime, critical information infrastructures and cyber-defence. One of the main trends transversal to these areas is the importance that the private sector has come to assume within them. In particular in the area of critical information infrastructure protection, the private sector is seen as a key stakeholder, given that it currently operates most infrastructures in this area. As a result of this operative capacity, the private sector has come to be understood as the expert in network and information systems security, whose knowledge is crucial for the regulation of the field. Adopting a Regulatory Capitalism framework, complemented by insights from Network Governance, we can identify the shifting role of the private sector in this field from one of a victim in need of protection in the first phase, to a commercial actor bearing responsibility for ensuring network resilience in the second, to an active policy shaper in the third, participating in the regulation of NIS by providing technical expertise. By drawing insights from the above-mentioned frameworks, we can better understand how private actors are involved in shaping regulatory responses, as well as why they have been incorporated into these regulatory networks.

Inappropriate oral formulations and information in paediatric trials

Previously, quality of formulations information provided for oral medications used in paediatric clinical trials published in 10 highly cited journals between 2002 and 2004 raised concerns. This short report explores if there was any subsequent improvement on how the formulations used in trials involving children

The influence of nutrient supply and cell density on the growth and survival of intervertebral disc cells in 3D culture

The adult human intervertebral disc (IVD) is normally avascular. Changes to the extracellular matrix in degenerative disc disease may promote vascularisation and subsequently alter cell nutrition and disc homeostasis. This study examines the influence of cell density and the presence of glucose and serum on the proliferation and survival of IVD cells in 3D culture. Bovine nucleus pulposus (NP) cells were seeded at a range of cell densities (1.25 × 10(5)-10(6) cells/mL) and cultured in alginate beads under standard culture conditions (with 3.15 g/L glucose and 10 % serum), or without glucose and/or 20% serum. Cell proliferation, apoptosis and cell senescence were examined after 8 days in culture. Under standard culture conditions, NP cell proliferation and cluster formation was inversely related to cell seeding density, whilst the number of apoptotic cells and enucleated "ghost" cells was positively correlated to cell seeding density. Increasing serum levels from 10% to 20% was associated with increased cluster size and also an increased prevalence of apoptotic cells within clusters. Omitting glucose produced even larger clusters and also more apoptotic and senescent cells. These studies demonstrate that NP cell growth and survival are influenced both by cell density and the availability of serum or nutrients, such as glucose. The observation of clustered, senescent, apoptotic or "ghost" cells in vitro suggests that environmental factors may influence the formation of these phenotypes that have been previously reported in vivo. Hence this study has implications for both our understanding of degenerative disc disease and also cell-based therapy using cells cultured in vitro.

A comparison of linear forecasting models and neural networks:an application to Euro inflation and Euro Divisia

Linear models reach their limitations in applications with nonlinearities in the data. In this paper new empirical evidence is provided on the relative Euro inflation forecasting performance of linear and non-linear models. The well established and widely used univariate ARIMA and multivariate VAR models are used as linear forecasting models whereas neural networks (NN) are used as non-linear forecasting models. It is endeavoured to keep the level of subjectivity in the NN building process to a minimum in an attempt to exploit the full potentials of the NN. It is also investigated whether the historically poor performance of the theoretically superior measure of the monetary services flow, Divisia, relative to the traditional Simple Sum measure could be attributed to a certain extent to the evaluation of these indices within a linear framework. Results obtained suggest that non-linear models provide better within-sample and out-of-sample forecasts and linear models are simply a subset of them. The Divisia index also outperforms the Simple Sum index when evaluated in a non-linear framework. © 2005 Taylor & Francis Group Ltd.

CEO compensation, option incentives and information disclosure

This paper examines the impact of information disclosure on the valuation of CEO options and the incentives created by those options. Prior executive compensation research in the US has made assumptions about key input variables that can affect the calculation of option values and financial incentives. Accordingly, biases may have ensued due to incomplete information disclosure about noncurrent option grants. Using new data on a sample of UK CEOs, we value executive option holdings and incentives for the first time and estimate the levels of distortion created by the less than complete US-style disclosure requirements. We also investigate the levels of distortion in the UK for the minority of companies that choose to reveal only partial information. Our results suggest that there have to date been few economic biases arising from less than complete information disclosure. Furthermore, we demonstrate that researchers using US data, who made reasonable assumptions about the inputs of noncurrent option grants, are unlikely to have made significant errors when calculating CEO financial incentives or option wealth. However, the recent downturn in the US stock market could result in the same assumptions, producing exaggerated incentive estimates in the future.