Developing a framework to evaluate business networks:the case of Ireland's industry-led network initiative

Business networks have been described as cooperative arrangements between independent business organisations that vary from contractual joint ventures to informal exchanges of information. This collaboration has become recognised as an innovative and efficient tool for organising interdependent activities, with benefits accruing to both firms and the local economy. For a number of years, resources have been devoted to supporting Irish networking policies. One recent example of such support is the Irish government's target of €20 million per annum for five years to support the creation of enterprise-led networks. It is imperative that a clear rationale for such interventions is established, as the opportunity cost of public funds is high. This article, therefore, develops an evaluation framework for such networking interventions. This framework will facilitate effective programme planning, implementation and evaluation. It will potentially show how a chain of cause-and-effect at both micro and macro-levels for networking interventions can be established.

Location and network effects on innovation success:evidence for UK, German and Irish manufacturing plants

Recent developments in the new economic geography and the literature on regional innovation systems have emphasised the potentially important role of networking and the characteristics of firms' local operating environment in shaping their innovative activity. Modeling UK, German and Irish plants' investments in R&D, technology transfer and networking, and their effect on the extent and success of plants' innovation activities, casts some doubt on the importance of both of these relationships. In particular, our analysis provides no support for the contention that firms or plants in the UK, Ireland or Germany with more strongly developed external links (collaborative networks or technology transfer) develop greater innovation intensity. However, although inter-firm links also have no effect on the commercial success of plants' innovation activity, intra-group links are important in terms of achieving commercial success. We also find evidence that R&D, technology transfer and networking inputs are substitutes rather than complements in the innovation process, and that there are systematic sectoral and regional influences in the efficiency with which such inputs are translated into innovation outputs. © 2001 Elsevier Science B.V.

Assessing the effectiveness of business support services in England:evidence from a theory based evaluation

In England, publicly supported advice to small firms is organized primarily through the Business Link (BL) network. Using the programme theory underlying this business support, we develop four propositions and test these empirically using data from a new survey of over 3000 English SMEs. We find strong support for the value to BL operators of a high profile to boost take-up. We find support for the BL’s market segmentation that targets intensive assistance to younger firms and those with limited liability. Allowing for sample selection, we find no significant effects on growth from ‘other’ assistance but find a significant employment boost from intensive assistance. This partially supports the programme theory assertion that BL improves business growth and strongly supports the proposition that there are differential outcomes from intensive and other assistance. This suggests an improvement in the BL network, compared with earlier studies, notably Roper et al. (2001), Roper and Hart (2005).

Development of reasoning:Behavioral evidence to support reinforcement over cognitive control accounts

Speed's theory makes two predictions for the development of analogical reasoning. Firstly, young children should not be able to reason analogically due to an undeveloped PFC neural network. Secondly, category knowledge enables the reinforcement of structural features over surface features, and thus the development of sophisticated, analogical, reasoning. We outline existing studies that support these predictions and highlight some critical remaining issues. Specifically, we argue that the development of inhibition must be directly compared alongside the development of reasoning strategies in order to support Speed's account. © 2010 Psychology Press.

Racing for radical innovation:how motorsport companies harness network diversity for discontinuous innovation

The motorsport industry is a significant part of the UK economy. According to industry estimates approximately 4,500 companies are involved in the UK Motorsport and Performance Engineering Industry and its wide-ranging support activities. The industry has an annual turnover of £6.0 billion, and contributes £3.6 billion worth of exports. The Motorsport Industry Association estimates that the support side of the sector alone "involving events management, public relations, marketing, sponsorship and a host of other support functions" accounts for approximately £1.7 billion of the yearly industry total. And in terms of employment, UK Motorsport supports 38,500 full and part-time jobs, including 25,000 engineers.

Communities and emerging semantics in semantic link network:discovery and learning

The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the Semantic Link Network (SLN), a loosely coupled semantic data model that can semantically link resources and derive out implicit semantic links according to a set of relational reasoning rules. By studying the intrinsic relationship between semantic communities and the semantic space of SLN, approaches to discovering reasoning-constraint, rule-constraint, and classification-constraint semantic communities are proposed. Further, the approaches, principles, and strategies for discovering emerging semantics in dynamic SLNs are studied. The basic laws of the semantic link network motion are revealed for the first time. An e-learning environment incorporating the proposed approaches, principles, and strategies to support effective discovery and learning is suggested.

Dynamic causal modeling of load-dependent modulation of effective connectivity within the verbal working memory network

Neuroimaging studies have consistently shown that working memory (WM) tasks engage a distributed neural network that primarily includes the dorsolateral prefrontal cortex, the parietal cortex, and the anterior cingulate cortex. The current challenge is to provide a mechanistic account of the changes observed in regional activity. To achieve this, we characterized neuroplastic responses in effective connectivity between these regions at increasing WM loads using dynamic causal modeling of functional magnetic resonance imaging data obtained from healthy individuals during a verbal n-back task. Our data demonstrate that increasing memory load was associated with (a) right-hemisphere dominance, (b) increasing forward (i.e., posterior to anterior) effective connectivity within the WM network, and (c) reduction in individual variability in WM network architecture resulting in the right-hemisphere forward model reaching an exceedance probability of 99% in the most demanding condition. Our results provide direct empirical support that task difficulty, in our case WM load, is a significant moderator of short-term plasticity, complementing existing theories of task-related reduction in variability in neural networks. Hum Brain Mapp, 2013. © 2013 Wiley Periodicals, Inc.

QoS guarantee with adaptive transmit power and message rate control for DSRC vehicle network based road safety applications

Quality of services (QoS) support is critical for dedicated short range communications (DSRC) vehicle networks based collaborative road safety applications. In this paper we propose an adaptive power and message rate control method for DSRC vehicle networks at road intersections. The design objective is to provide high availability and low latency channels for high priority emergency safety applications while maximizing channel utilization for low priority routine safety applications. In this method an offline simulation based approach is used to find out the best possible configurations of transmit power and message rate for given numbers of vehicles in the network. The identified best configurations are then used online by roadside access points (AP) according to estimated number of vehicles. Simulation results show that this adaptive method significantly outperforms a fixed control method. © 2011 Springer-Verlag.

Networks of Evolutionary Processors (NEP) as Decision Support Systems

This paper presents the application of Networks of Evolutionary Processors to Decision Support Systems, precisely Knowledge-Driven DSS. Symbolic information and rule-based behavior in Networks of Evolutionary Processors turn out to be a great tool to obtain decisions based on objects present in the network. The non-deterministic and massive parallel way of operation results in NP-problem solving in linear time. A working NEP example is shown.

Indirect ties in knowledge networks:a social network analysis with ordered weighted averaging operators

This PhD thesis analyses networks of knowledge flows, focusing on the role of indirect ties in the knowledge transfer, knowledge accumulation and knowledge creation process. It extends and improves existing methods for mapping networks of knowledge flows in two different applications and contributes to two stream of research. To support the underlying idea of this thesis, which is finding an alternative method to rank indirect network ties to shed a new light on the dynamics of knowledge transfer, we apply Ordered Weighted Averaging (OWA) to two different network contexts. Knowledge flows in patent citation networks and a company supply chain network are analysed using Social Network Analysis (SNA) and the OWA operator. The OWA is used here for the first time (i) to rank indirect citations in patent networks, providing new insight into their role in transferring knowledge among network nodes; and to analyse a long chain of patent generations along 13 years; (ii) to rank indirect relations in a company supply chain network, to shed light on the role of indirectly connected individuals involved in the knowledge transfer and creation processes and to contribute to the literature on knowledge management in a supply chain. In doing so, indirect ties are measured and their role as means of knowledge transfer is shown. Thus, this thesis represents a first attempt to bridge the OWA and SNA fields and to show that the two methods can be used together to enrich the understanding of the role of indirectly connected nodes in a network. More specifically, the OWA scores enrich our understanding of knowledge evolution over time within complex networks. Future research can show the usefulness of OWA operator in different complex networks, such as the on-line social networks that consists of thousand of nodes.

A decision support system for waste collection management and its potential improvement with Radio-Frequency Identification Technology (RFID)

Due to vigorous globalisation and product proliferation in recent years, more waste has been produced by the soaring manufacturing activities. This has contributed to the significant need for an efficient waste management system to ensure, with all efforts, the waste is properly treated for recycling or disposed. This paper presents a Decision Support System (DSS) framework, based on Constraint Logic Programming (CLP), for the collection management of industrial waste (of all kinds) and discusses the potential employment of Radio-Frequency Identification Technology (RFID) to improve several critical procedures involved in managing waste collection. This paper also demonstrates a widely distributed and semi-structured network of waste producing enterprises (e.g. manufacturers) and waste processing enterprises (i.e. waste recycling/treatment stations) improving their operations planning by means of using the proposed DSS. The potential RFID applications to update and validate information in a continuous manner to bring value-added benefits to the waste collection business are also presented. © 2012 Inderscience Enterprises Ltd.

Semantic enabled sensor network design

Wireless Sensor Network (WSN) systems have become more and more popular in our modern life. They have been widely used in many areas, such as smart homes/buildings, context-aware devices, military applications, etc. Despite the increasing usage, there is a lack of formal description and automated verification for WSN system design. In this paper, we present an approach to support the rigorous verification of WSN modeling using the Semantic Web technology We use Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) to define a meta-ontology for the modeling of WSN systems. Furthermore, we apply ontology reasoners to perform automated verification on customized WSN models and their instances. We demonstrate and evaluate our approach through a Light Control System (LCS) as the case study.

Understanding inter-firm networks and types of innovation in SMEs:a social network perspective

Innovation is one of the key drivers for gaining competitive advantages in any firms. Understanding knowledge transfer through inter-firm networks and its effects on types of innovation in SMEs is very important in improving SMEs innovation. This study examines relationships between characteristics of inter-firm knowledge transfer networks and types of innovation in SMEs. To achieve this, social network perspective is adopted to understand inter-firm knowledge transfer networks and its impact on innovation by investigating how and to what extend ego network characteristics are affecting types of innovation. Therefore, managers can develop the firms'network according to their strategies and requirements. First, a conceptual model and research hypotheses are proposed to establish the possible relationship between network properties and types of innovation. Three aspects of ego network are identified and adopted for hypotheses development: 1) structural properties which address the potential for resources and the context for the flow of resources, 2) relational properties which reflect the quality of resource flows, and 3) nodal properties which are about quality and variety of resources and capabilities of the ego partners. A questionnaire has been designed based on the hypotheses. Second, semistructured interviews with managers of five SMEs have been carried out, and a thematic qualitative analysis of these interviews has been performed. The interviews helped to revise the questionnaire and provided preliminary evidence to support the hypotheses. Insights from the preliminary investigation also helped to develop research plan for the next stage of this research.

Advanced predictive-analysis-based decision support for collaborative logistics networks

Purpose – The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution. Design/methodology/approach – The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments. Findings – Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes. Practical implications – The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept. Originality/value – The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

Abstractions to support dynamic adaptation of communication frameworks for user-centric communication

The convergence of data, audio and video on IP networks is changing the way individuals, groups and organizations communicate. This diversity of communication media presents opportunities for creating synergistic collaborative communications. This form of collaborative communication is however not without its challenges. The increasing number of communication service providers coupled with a combinatorial mix of offered services, varying Quality-of-Service and oscillating pricing of services increases the complexity for the user to manage and maintain ‘always best’ priced or performance services. Consumers have to manually manage and adapt their communication in line with differences in services across devices, networks and media while ensuring that the usage remain consistent with their intended goals. This dissertation proposes a novel user-centric approach to address this problem. The proposed approach aims to reduce the aforementioned complexity to the user by (1) providing high-level abstractions and a policy based methodology for automated selection of the communication services guided by high-level user policies and (2) providing services through the seamless integration of multiple communication service providers and providing an extensible framework to support the integration of multiple communication service providers. The approach was implemented in the Communication Virtual Machine (CVM), a model-driven technology for realizing communication applications. The CVM includes the Network Communication Broker, the layer responsible for providing a network-independent API to the upper layers of CVM. The initial prototype for the NCB supported only a single communication framework which limited the number, quality and types of services available. Experimental evaluation of the approach show the additional overhead of the approach is minimal compared to the individual communication services frameworks. Additionally the automated approach proposed out performed the individual communication services frameworks for cross framework switching.