Informal communication networks and the diffusion of innovations in UK construction projects: A research design

The UK industry has been criticised for being slow to adopt construction process innovations. Research shows that the idiosyncrasies of participants, their roles in the system and the contextual differences between sections of the industry make this a highly complex problem. There is considerable evidence that informal social networks play a key role in diffusion of innovations. The aim is to identify informal communication networks of project participants and the role these play in the diffusion of construction innovations. The characteristics of this network will be analysed in order to understand how they can be used to accelerate innovation diffusion within and between projects. Social Network Analysis is used to determine informal communication routes. Control and experiment case study projects are used within two different organizations. This allows informal communication routes concerning innovations to be mapped, whilst testing if the informal routes can facilitate diffusion. Analysis will focus upon understanding the combination of informal strong and weak ties, and how these impede or facilitate the diffusion of the innovation. Initial work suggests the presence of an informal communication network. Actors within this informal network, and the organization's management are unaware of its' existence and their informal roles within it. Thus, the network remains an untapped medium regarding innovation diffusion. It is proposed that successful innovation diffusion is dependent upon understanding informal strong and weak ties, at project, organization and industry level.

Horses for courses: Relating innovation diffusion concepts to the stage of the diffusion process

The research uses a sociological perspective to build an improved, context specific understanding of innovation diffusion within the UK construction industry. It is argued there is an iterative interplay between actors and the social system they occupy that directly influences the diffusion process as well as the methodology adopted. The research builds upon previous findings that argued a level of best fit for the three innovation diffusion concepts of cohesion, structural equivalence and thresholds. That level of best fit is analysed here using empirical data from the UK construction industry. This analysis allows an understanding of how the relative importance of these concepts' actually varies within the stages of the innovation diffusion process. The conclusion that the level of relevance fluctuates in relation to the stages of the diffusion process is a new development in the field.

The diffusion of innovations within a UKCI context: An explanatory framework

The UK Construction Industry has been criticized for being slow to change and adopt innovations. The idiosyncrasies of participants, their roles in a social system and the contextual differences between sections of the UK Construction Industry are viewed as being paramount to explaining innovation diffusion within this context. Three innovation diffusion theories from outside construction management literature are introduced, Cohesion, Structural Equivalence and Thresholds. The relevance of each theory, in relation to the UK Construction Industry, is critically reviewed using literature and empirical data. Analysis of the data results in an explanatory framework being proposed. The framework introduces a Personal Awareness Threshold concept, highlights the dominant role of Cohesion through the main stages of diffusion, together with the use of Structural Equivalence during the later stages of diffusion and the importance of Adoption Threshold levels.

Minimum stable convergence criteria for stochastic diffusion search

An analysis of Stochastic Diffusion Search (SDS), a novel and efficient optimisation and search algorithm, is presented, resulting in a derivation of the minimum acceptable match resulting in a stable convergence within a noisy search space. The applicability of SDS can therefore be assessed for a given problem.

Communicating neurons: a connectionist spiking neuron implementation of stochastic diffusion search

An information processing paradigm in the brain is proposed, instantiated in an artificial neural network using biologically motivated temporal encoding. The network will locate within the external world stimulus, the target memory, defined by a specific pattern of micro-features. The proposed network is robust and efficient. Akin in operation to the swarm intelligence paradigm, stochastic diffusion search, it will find the best-fit to the memory with linear time complexity. information multiplexing enables neurons to process knowledge as 'tokens' rather than 'types'. The network illustrates possible emergence of cognitive processing from low level interactions such as memory retrieval based on partial matching. (C) 2007 Elsevier B.V. All rights reserved.

Analyzing diffusion tensor images with ghosting artifacts: the effects of direct and indirect normalization

The current study aims to assess the applicability of direct or indirect normalization for the analysis of fractional anisotropy (FA) maps in the context of diffusion-weighted images (DWIs) contaminated by ghosting artifacts. We found that FA maps acquired by direct normalization showed generally higher anisotropy than indirect normalization, and the disparities were aggravated by the presence of ghosting artifacts in DWIs. The voxel-wise statistical comparisons demonstrated that indirect normalization reduced the influence of artifacts and enhanced the sensitivity of detecting anisotropy differences between groups. This suggested that images contaminated with ghosting artifacts can be sensibly analyzed using indirect normalization.

Mechanistic insights into a gas–solid reaction in molecular crystals: the role of hydrogen bonding

Reactions in (molecular) organic crystalline solids have been shown to be important for exerting control that is unattainable over chemical transformations in solution. Such control has also been achieved for reactions within metal– organic cages. In these examples, the reactants are already in place within the crystals following the original crystal growth. The post-synthetic modification of metal–organic frameworks (MOFs and indeed reactions and catalysis within MOFs have been recently demonstrated; in these cases the reactants enter the crystals through permanent channels. Another growing area of interest within molecular solid-state chemistry is synthesis by mechanical co-grinding of solid reactants—often referred to as mechanochemistry. Finally, in a small number of reported examples, molecules also have been shown to enter nonporous crystals directly from the gas or vapor phase, but in only a few of these examples does a change in covalent bonding result, which indicates that a reaction occurs within the nonporous crystals. It is this latter type of highly uncommon reaction that is the focus of the present study.

Self-assembled healable materials through a combination of pi-pi stacking and hydrogen bonding

The discovery of polymers with stimuli responsive physical properties is a rapidly expanding area of research. At the forefront of the field are self-healing polymers, which, when fractured can regain the mechanical properties of the material either autonomically, or in response to a stimulus. It has long been known that it is possible to promote healing in conventional thermoplastics by heating the fracture zone above the Tg of the polymer under pressure. This process requires reptation and subsequent re-entanglement of macromolecules across the fracture void, which serves to bridge, and ‘heal’ the crack. The timescale for this mechanism is highly dependent on the molecular weight of the polymer being studied. This process is in contrast to that required to affect healing in supramolecular polymers such as the plasticised, hydrogen bonded elastomer reported by Leibler et al. The disparity in bond energies between the non-covalent and covalent bonds within supramolecular polymers results in fractures propagating through scission of the comparatively weak supramolecular interactions, rather than through breaking the stronger, covalent bonds. Thus, during the healing process the macromolecules surrounding the fracture site only need sufficient energy to re-engage their supramolecular interactions in order to regenerate the strength of the pristine material. Herein we describe the design, synthesis and optimization of a new class of supramolecular polymer blends that harness the reversible nature of pi-pi stacking and hydrogen bonding interactions to produce self-supporting films with facile healable characteristics.