The evolution of innovation capability in multinational enterprise subsidiaries: dual network embeddedness and the divergence of subsidiary specialisation in Taiwan

This paper examines how innovation-related capabilities for production, design and marketing develop at the subsidiary level within multinational enterprises (MNEs). We focus on how subsidiary autonomy and changing opportunities to access internal (MNE) and external (host country) sources of capability contribute in a combined way to the accumulation of specialist capabilities in five Taiwan-based MNE subsidiaries in the semiconductor industry. Longitudinal analysis shows how the accumulation process is subject to discontinuities, as functional divisions are (re)opened and closed during the lifetime of the subsidiary. A composite set of innovation output measures also shows significant variations in within-function levels of capability across our sample. We conclude that subsidiary specialisation and unique subsidiary-specific advantages have evolved in a way that is strongly influenced by the above factors.

GDASH: a grid-enabled program for structure solution from powder diffraction data

The simulated annealing approach to structure solution from powder diffraction data, as implemented in the DASH program, is easily amenable to parallelization at the individual run level. Very large scale increases in speed of execution can therefore be achieved by distributing individual DASH runs over a network of computers. The GDASH program achieves this by packaging DASH in a form that enables it to run under the Univa UD Grid MP system, which harnesses networks of existing computing resources to perform calculations.

Innovation dynamics and capability in open collaborative cyber communities: implications for cybersecurity

Cybersecurity is a complex challenge that has emerged alongside the evolving global socio-technical environment of social networks that feature connectivity across time and space in ways unimaginable even a decade ago. This paper reports on the preliminary findings of a NATO funded project that investigates the nature of innovation in open collaborative communities and its implications for cyber security. In this paper, the authors describe the framing of relevant issues, the articulation of the research questions, and the derivation of a conceptual framework based on open collaborative innovation that has emerged from preliminary field research in Russia and the UK.

A neurofuzzy network knowledge extraction and extended gram-Schmidt algorithm for model subspace decomposition

This paper introduces a new neurofuzzy model construction and parameter estimation algorithm from observed finite data sets, based on a Takagi and Sugeno (T-S) inference mechanism and a new extended Gram-Schmidt orthogonal decomposition algorithm, for the modeling of a priori unknown dynamical systems in the form of a set of fuzzy rules. The first contribution of the paper is the introduction of a one to one mapping between a fuzzy rule-base and a model matrix feature subspace using the T-S inference mechanism. This link enables the numerical properties associated with a rule-based matrix subspace, the relationships amongst these matrix subspaces, and the correlation between the output vector and a rule-base matrix subspace, to be investigated and extracted as rule-based knowledge to enhance model transparency. The matrix subspace spanned by a fuzzy rule is initially derived as the input regression matrix multiplied by a weighting matrix that consists of the corresponding fuzzy membership functions over the training data set. Model transparency is explored by the derivation of an equivalence between an A-optimality experimental design criterion of the weighting matrix and the average model output sensitivity to the fuzzy rule, so that rule-bases can be effectively measured by their identifiability via the A-optimality experimental design criterion. The A-optimality experimental design criterion of the weighting matrices of fuzzy rules is used to construct an initial model rule-base. An extended Gram-Schmidt algorithm is then developed to estimate the parameter vector for each rule. This new algorithm decomposes the model rule-bases via an orthogonal subspace decomposition approach, so as to enhance model transparency with the capability of interpreting the derived rule-base energy level. This new approach is computationally simpler than the conventional Gram-Schmidt algorithm for resolving high dimensional regression problems, whereby it is computationally desirable to decompose complex models into a few submodels rather than a single model with large number of input variables and the associated curse of dimensionality problem. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

Improving CS-4 user data rate in GPRS enabled devices by using a BLER co-processor

The General Packet Radio Service (GPRS) was developed to allow packet data to be transported efficiently over an existing circuit switched radio network. The main applications for GPRS are in transporting IP datagram’s from the user’s mobile Internet browser to and from the Internet, or in telemetry equipment. A simple Error Detection and Correction (EDC) scheme to improve the GPRS Block Error Rate (BLER) performance is presented, particularly for coding scheme 4 (CS-4), however gains in other coding schemes are seen. For every GPRS radio block that is corrected by the EDC scheme, the block does not need to be retransmitted releasing bandwidth in the channel, improving throughput and the user’s application data rate. As GPRS requires intensive processing in the baseband, a viable hardware solution for a GPRS BLER co-processor is discussed that has been currently implemented in a Field Programmable Gate Array (FPGA) and presented in this paper.

Cloud optical depth retrievals from the Aerosol Robotic Network (AERONET) cloud mode observations

Cloud optical depth is one of the most poorly observed climate variables. The new “cloud mode” capability in the Aerosol Robotic Network (AERONET) will inexpensively yet dramatically increase cloud optical depth observations in both number and accuracy. Cloud mode optical depth retrievals from AERONET were evaluated at the Atmospheric Radiation Measurement program’s Oklahoma site in sky conditions ranging from broken clouds to overcast. For overcast cases, the 1.5 min average AERONET cloud mode optical depths agreed to within 15% of those from a standard ground‐based flux method. For broken cloud cases, AERONET retrievals also captured rapid variations detected by the microwave radiometer. For 3 year climatology derived from all nonprecipitating clouds, AERONET monthly mean cloud optical depths are generally larger than cloud radar retrievals because of the current cloud mode observation strategy that is biased toward measurements of optically thick clouds. This study has demonstrated a new way to enhance the existing AERONET infrastructure to observe cloud optical properties on a global scale.

Normality mining: privacy implications of behavioral profiles drawn from GPS enabled mobile phones

There is growing interest in the ways in which the location of a person can be utilized by new applications and services. Recent advances in mobile technologies have meant that the technical capability to record and transmit location data for processing is appearing in off-the-shelf handsets. This opens possibilities to profile people based on the places they visit, people they associate with, or other aspects of their complex routines determined through persistent tracking. It is possible that services offering customized information based on the results of such behavioral profiling could become commonplace. However, it may not be immediately apparent to the user that a wealth of information about them, potentially unrelated to the service, can be revealed. Further issues occur if the user agreed, while subscribing to the service, for data to be passed to third parties where it may be used to their detriment. Here, we report in detail on a short case study tracking four people, in three European member states, persistently for six weeks using mobile handsets. The GPS locations of these people have been mined to reveal places of interest and to create simple profiles. The information drawn from the profiling activity ranges from intuitive through special cases to insightful. In this paper, these results and further extensions to the technology are considered in light of European legislation to assess the privacy implications of this emerging technology.

A new South American network to study the atmospheric electric field and its variations related to geophysical phenomena

In this paper we present the capability of a new network of field mill sensors to monitor the atmospheric electric field at various locations in South America; we also show some early results. The main objective of the new network is to obtain the characteristic Universal Time diurnal curve of the atmospheric electric field in fair weather, known as the Carnegie curve. The Carnegie curve is closely related to the current sources flowing in the Global Atmospheric Electric Circuit so that another goal is the study of this relationship on various time scales (transient/monthly/seasonal/annual). Also, by operating this new network, we may also study departures of the Carnegie curve from its long term average value related to various solar, geophysical and atmospheric phenomena such as the solar cycle, solar flares and energetic charged particles, galactic cosmic rays, seismic activity and specific meteorological events. We then expect to have a better understanding of the influence of these phenomena on the Global Atmospheric Electric Circuit and its time-varying behavior.

A robust two-dimensional hydrogen-bonded network for the predictable assembly of ternary co-crystals of furosemide

Consideration of the geometrical features of the functional groups present in furosemide has enabled synthesis of a series of ternary co-crystals with predictable structural features, containing a robust asymmetric two-dimensional network.

Towards a framework for managing IT-enabled change, sourcing and governance

In the resource-based view, organisations are represented by the sum of their physical, human and organisational assets, resources and capabilities. Operational capabilities maintain the status quo and allow an organisation to execute their existing business. Dynamic capabilities, otherwise, allow an organisation to change this status quo including a change of the operational ones. Competitive advantage, in this context, is an effect of continuously developing and reconfiguring these firm-specific assets through dynamic capabilities. Deciding where and how to source the core operational capabilities is a key success factor. Furthermore, developing its dynamic capabilities allows an organisation to effectively manage change its operational capabilities. Many organisations are asserted to have a high dependency on - as well as a high benefit from - the use of information technology (IT), making it a crucial and overarching resource. Furthermore, the IT function is assigned the role as a change enabler and so IT sourcing affects the capability of managing business change. IT sourcing means that organisations need to decide how to source their IT capabilities. Outsourcing of parts of the IT function will also outsource some of the IT capabilities and therefore some of the business capabilities. As a result, IT sourcing has an impact on the organisation's capabilities and consequently on the business success. And finally, a turbulent and fast moving business environment challenges organisations to effectively and efficiently managing business change. Our research builds on the existing theory of dynamic and operational capabilities by considering the interdependencies between the dynamic capabilities of business change and IT sourcing. Further it examines the decision-making oversight of these areas as implemented through IT governance. We introduce a new conceptual framework derived from the existing theory and extended through an illustrative case study conducted in a German bank. Under a philosophical paradigm of constructivism, we collected data from eight semi-structured interviews and used additional sources of evidence in form of annual accounts, strategy papers and IT benchmark reports. We applied an Interpretative Phenomenological Analysis (IPA), which emerged the superordinate themes for our tentative capabilities framework. An understanding of these interdependencies enables scholars and professionals to improve business success through effectively managing business change and evaluating the impact of IT sourcing decisions on the organisation's operational and dynamic capabilities.

Time to act: the UK in NATO

Since 1989, NATO has expanded its strategic concept and geopolitical scope to the detriment of an efficient and well-defined military capability in Europe. The Ukrainian crisis has brought the attention back to Europe and to NATO’s deterrent value. As one of the Alliance’s leading members, Britain must act as a catalyst to ensure that NATO has the necessary military strength and political will to respond to the new security challenges.

CDASH: a cloud-enabled program for structure solution from powder diffraction data

The simulated annealing approach to crystal structure determination from powder diffraction data, as implemented in the DASH program, is readily amenable to parallelization at the individual run level. Very large scale increases in speed of execution can be achieved by distributing individual DASH runs over a network of computers. The CDASH program delivers this by using scalable on-demand computing clusters built on the Amazon Elastic Compute Cloud service. By way of example, a 360 vCPU cluster returned the crystal structure of racemic ornidazole (Z0 = 3, 30 degrees of freedom) ca 40 times faster than a typical modern quad-core desktop CPU. Whilst used here specifically for DASH, this approach is of general applicability to other packages that are amenable to coarse-grained parallelism strategies.

Relational architecture and relational capability: organisational levers to support strategic supplier relationships

The resource based view of strategy suggests that competitiveness in part derives from a firms ability to collaborate with a subset of its supply network to co-create highly valued products and services. This relational capability relies on a foundational intra and inter-organisational architecture, the manifestation of strategic, people, and process decisions facilitating the interface between the firm and its strategic suppliers. Using covariance-based structural equation modelling we examine the relationships between internal and external features of relational architecture, and their relationship with relational capability and relational quality. This is undertaken on data collected by mail survey. We find significant relationships between both internal and external relational architecture and relational capability and between relational capability and relational quality. Novel constructs for internal and external elements of relational architecture are specified to demonstrate their positive influence on relational capability and relationship quality.