A study of inputs and their influence on technological innovative activity

Technological innovation has been widely studied: however surprisingly little is known about the experience of managing the process. Most reports tend to be generalistic and/or prescriptive whereas it is argued that multiple sources of variation in the process limit the value of these. A description of the innovation process is given together with a presentation of what is knovrn from existing studies. Gaps identified in this area suggest that a variety of organisational influences are important and an attempt is made to identify some of these at individual, group and organisational level. A simple system model of the innovation management process is developed. Further investigation of the influence of these factors was made possible through an extended on-site case study. Methodology for this based upon participant observation coupled wth a wide and flexible range of techniques is described. Evidence is presented about many aspects of the innovation process from a number of different levels and perspectives: the attempt is to demonstrate the extent to which variation due to contingent influences takes place. It is argued that problems identified all relate to the issue of integration. This theme is also developed from an analytical viewoint and it is suggested that organisational response to increases in complexity in the external environment will be to match them with internal complexity. Differentiation of this kind will require extensive and flexible integration, especially in those inherently uncertain areas associated with innovation. Whilst traditionally a function of management, it is argued that integration needs have increased to the point where a new specialism is required. The concept of integration specialist is developed from this analysis and attempts at simple integrative change during the research are described. Finally a strategy for integration - or rather for building in integrative capability - ln the organisation studied is described.

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

A linear relational DEA model to evaluate two-stage processes with shared inputs

Two-stage data envelopment analysis (DEA) efficiency models identify the efficient frontier of a two-stage production process. In some two-stage processes, the inputs to the first stage are shared by the second stage, known as shared inputs. This paper proposes a new relational linear DEA model for dealing with measuring the efficiency score of two-stage processes with shared inputs under constant returns-to-scale assumption. Two case studies of banking industry and university operations are taken as two examples to illustrate the potential applications of the proposed approach.