Is more capability always beneficial for firm performance? Market orientation, core business process capabilities, and business environment

This study examines the role of capabilities in core marketing-related business processes–product development management (PDM), supply chain management (SCM) and customer relationship management (CRM)–in translating a firm’s market orientation (MO) into firm performance. The study is the first to examine the interplay of all three business process capabilities simultaneously, while investigating how environmental conditions moderate their performance effects. A moderated mediation analysis of 468 product-focused firms finds that PDM and CRM process capabilities play important mediating roles, whereas SCM process capability does not mediate the relationship between MO and performance. However, the relative importance of the capabilities as mediators varies along the degree of environmental turbulence, and under certain conditions, an increase in the level of business process capability may even turn detrimental.

Regularisation of mixture density networks

Mixture Density Networks are a principled method to model conditional probability density functions which are non-Gaussian. This is achieved by modelling the conditional distribution for each pattern with a Gaussian Mixture Model for which the parameters are generated by a neural network. This thesis presents a novel method to introduce regularisation in this context for the special case where the mean and variance of the spherical Gaussian Kernels in the mixtures are fixed to predetermined values. Guidelines for how these parameters can be initialised are given, and it is shown how to apply the evidence framework to mixture density networks to achieve regularisation. This also provides an objective stopping criteria that can replace the `early stopping' methods that have previously been used. If the neural network used is an RBF network with fixed centres this opens up new opportunities for improved initialisation of the network weights, which are exploited to start training relatively close to the optimum. The new method is demonstrated on two data sets. The first is a simple synthetic data set while the second is a real life data set, namely satellite scatterometer data used to infer the wind speed and wind direction near the ocean surface. For both data sets the regularisation method performs well in comparison with earlier published results. Ideas on how the constraint on the kernels may be relaxed to allow fully adaptable kernels are presented.

Regularisation of mixture density networks

Mixture Density Networks are a principled method to model conditional probability density functions which are non-Gaussian. This is achieved by modelling the conditional distribution for each pattern with a Gaussian Mixture Model for which the parameters are generated by a neural network. This thesis presents a novel method to introduce regularisation in this context for the special case where the mean and variance of the spherical Gaussian Kernels in the mixtures are fixed to predetermined values. Guidelines for how these parameters can be initialised are given, and it is shown how to apply the evidence framework to mixture density networks to achieve regularisation. This also provides an objective stopping criteria that can replace the `early stopping' methods that have previously been used. If the neural network used is an RBF network with fixed centres this opens up new opportunities for improved initialisation of the network weights, which are exploited to start training relatively close to the optimum. The new method is demonstrated on two data sets. The first is a simple synthetic data set while the second is a real life data set, namely satellite scatterometer data used to infer the wind speed and wind direction near the ocean surface. For both data sets the regularisation method performs well in comparison with earlier published results. Ideas on how the constraint on the kernels may be relaxed to allow fully adaptable kernels are presented.

UncertML: an XML schema for exchanging uncertainty

Authors from Burrough (1992) to Heuvelink et al. (2007) have highlighted the importance of GIS frameworks which can handle incomplete knowledge in data inputs, in decision rules and in the geometries and attributes modelled. It is particularly important for this uncertainty to be characterised and quantified when GI data is used for spatial decision making. Despite a substantial and valuable literature on means of representing and encoding uncertainty and its propagation in GI (e.g.,Hunter and Goodchild 1993; Duckham et al. 2001; Couclelis 2003), no framework yet exists to describe and communicate uncertainty in an interoperable way. This limits the usability of Internet resources of geospatial data, which are ever-increasing, based on specifications that provide frameworks for the ‘GeoWeb’ (Botts and Robin 2007; Cox 2006). In this paper we present UncertML, an XML schema which provides a framework for describing uncertainty as it propagates through many applications, including online risk management chains. This uncertainty description ranges from simple summary statistics (e.g., mean and variance) to complex representations such as parametric, multivariate distributions at each point of a regular grid. The philosophy adopted in UncertML is that all data values are inherently uncertain, (i.e., they are random variables, rather than values with defined quality metadata).

Income distribution dependence of poverty measure:a theoretical analysis

Using a modified deprivation (or poverty) function, in this paper, we theoretically study the changes in poverty with respect to the 'global' mean and variance of the income distribution using Indian survey data. We show that when the income obeys a log-normal distribution, a rising mean income generally indicates a reduction in poverty while an increase in the variance of the income distribution increases poverty. This altruistic view for a developing economy, however, is not tenable anymore once the poverty index is found to follow a pareto distribution. Here although a rising mean income indicates a reduction in poverty, due to the presence of an inflexion point in the poverty function, there is a critical value of the variance below which poverty decreases with increasing variance while beyond this value, poverty undergoes a steep increase followed by a decrease with respect to higher variance. Identifying this inflexion point as the poverty line, we show that the pareto poverty function satisfies all three standard axioms of a poverty index [N.C. Kakwani, Econometrica 43 (1980) 437; A.K. Sen, Econometrica 44 (1976) 219] whereas the log-normal distribution falls short of this requisite. Following these results, we make quantitative predictions to correlate a developing with a developed economy. © 2006 Elsevier B.V. All rights reserved.

Targets and self monitoring in hypertension: randomised controlled trial and cost effectiveness analysis

OBJECTIVES: To assess whether blood pressure control in primary care could be improved with the use of patient held targets and self monitoring in a practice setting, and to assess the impact of these on health behaviours, anxiety, prescribed antihypertensive drugs, patients' preferences, and costs. DESIGN: Randomised controlled trial. SETTING: Eight general practices in south Birmingham. PARTICIPANTS: 441 people receiving treatment in primary care for hypertension but not controlled below the target of < 140/85 mm Hg. INTERVENTIONS: Patients in the intervention group received treatment targets along with facilities to measure their own blood pressure at their general practice; they were also asked to visit their general practitioner or practice nurse if their blood pressure was repeatedly above the target level. Patients in the control group received usual care (blood pressure monitoring by their practice). MAIN OUTCOME MEASURES: Primary outcome: change in systolic blood pressure at six months and one year in both intervention and control groups. Secondary outcomes: change in health behaviours, anxiety, prescribed antihypertensive drugs, patients' preferences of method of blood pressure monitoring, and costs. RESULTS: 400 (91%) patients attended follow up at one year. Systolic blood pressure in the intervention group had significantly reduced after six months (mean difference 4.3 mm Hg (95% confidence interval 0.8 mm Hg to 7.9 mm Hg)) but not after one year (mean difference 2.7 mm Hg (- 1.2 mm Hg to 6.6 mm Hg)). No overall difference was found in diastolic blood pressure, anxiety, health behaviours, or number of prescribed drugs. Patients who self monitored lost more weight than controls (as evidenced by a drop in body mass index), rated self monitoring above monitoring by a doctor or nurse, and consulted less often. Overall, self monitoring did not cost significantly more than usual care (251 pounds sterling (437 dollars; 364 euros) (95% confidence interval 233 pounds sterling to 275 pounds sterling) versus 240 pounds sterling (217 pounds sterling to 263 pounds sterling). CONCLUSIONS: Practice based self monitoring resulted in small but significant improvements of blood pressure at six months, which were not sustained after a year. Self monitoring was well received by patients, anxiety did not increase, and there was no appreciable additional cost. Practice based self monitoring is feasible and results in blood pressure control that is similar to that in usual care.

Managing uncertainty in complex stochastic models: design and emulation of a Rabies model

In this paper we present a novel method for emulating a stochastic, or random output, computer model and show its application to a complex rabies model. The method is evaluated both in terms of accuracy and computational efficiency on synthetic data and the rabies model. We address the issue of experimental design and provide empirical evidence on the effectiveness of utilizing replicate model evaluations compared to a space-filling design. We employ the Mahalanobis error measure to validate the heteroscedastic Gaussian process based emulator predictions for both the mean and (co)variance. The emulator allows efficient screening to identify important model inputs and better understanding of the complex behaviour of the rabies model.

Intelligent execution monitoring and error analysis in planning involving processes

An intelligent agent, operating in an external world which cannot be fully described in its internal world model, must be able to monitor the success of a previously generated plan and to respond to any errors which may have occurred. The process of error analysis requires the ability to reason in an expert fashion about time and about processes occurring in the world. Reasoning about time is needed to deal with causality. Reasoning about processes is needed since the direct effects of a plan action can be completely specified when the plan is generated, but the indirect effects cannot. For example, the action `open tap' leads with certainty to `tap open', whereas whether there will be a fluid flow and how long it might last is more difficult to predict. The majority of existing planning systems cannot handle these kinds of reasoning, thus limiting their usefulness. This thesis argues that both kinds of reasoning require a complex internal representation of the world. The use of Qualitative Process Theory and an interval-based representation of time are proposed as a representation scheme for such a world model. The planning system which was constructed has been tested on a set of realistic planning scenarios. It is shown that even simple planning problems, such as making a cup of coffee, require extensive reasoning if they are to be carried out successfully. The final Chapter concludes that the planning system described does allow the correct solution of planning problems involving complex side effects, which planners up to now have been unable to solve.

Heterogeneous catalysts for clean technology:spectroscopy, design, and monitoring

Reactive, but not a reactant. Heterogeneous catalysts play an unseen role in many of today's processes and products. With the increasing emphasis on sustainability in both products and processes, this handbook is the first to combine the hot topics of heterogeneous catalysis and clean technology. It focuses on the development of heterogeneous catalysts for use in clean chemical synthesis, dealing with how modern spectroscopic techniques can aid the design of catalysts for use in liquid phase reactions, their application in industrially important chemistries - including selective oxidation, hydrogenation, solid acid- and base-catalyzed processes - as well as the role of process intensification and use of renewable resources in improving the sustainability of chemical processes. With its emphasis on applications, this book is of high interest to those working in the industry.

Project risk management:a combined analytic hierarchy process and decision tree approach

Time, cost and quality achievements on large-scale construction projects are uncertain because of technological constraints, involvement of many stakeholders, long durations, large capital requirements and improper scope definitions. Projects that are exposed to such an uncertain environment can effectively be managed with the application of risk management throughout the project life cycle. Risk is by nature subjective. However, managing risk subjectively poses the danger of non-achievement of project goals. Moreover, risk analysis of the overall project also poses the danger of developing inappropriate responses. This article demonstrates a quantitative approach to construction risk management through an analytic hierarchy process (AHP) and decision tree analysis. The entire project is classified to form a few work packages. With the involvement of project stakeholders, risky work packages are identified. As all the risk factors are identified, their effects are quantified by determining probability (using AHP) and severity (guess estimate). Various alternative responses are generated, listing the cost implications of mitigating the quantified risks. The expected monetary values are derived for each alternative in a decision tree framework and subsequent probability analysis helps to make the right decision in managing risks. In this article, the entire methodology is explained by using a case application of a cross-country petroleum pipeline project in India. The case study demonstrates the project management effectiveness of using AHP and DTA.

A methodology for the generation and evaluation of biorefinery process chains, in order to identify the most promising biorefineries for the EU

The topic of bioenergy, biofuels and bioproducts remains at the top of the current political and research agenda. Identification of the optimum processing routes for biomass, in terms of efficiency, cost, environment and socio-economics is vital as concern grows over the remaining fossil fuel resources, climate change and energy security. It is known that the only renewable way of producing conventional hydrocarbon fuels and organic chemicals is from biomass, but the problem remains of identifying the best product mix and the most efficient way of processing biomass to products. The aim is to move Europe towards a biobased economy and it is widely accepted that biorefineries are key to this development. A methodology was required for the generation and evaluation of biorefinery process chains for converting biomass into one or more valuable products that properly considers performance, cost, environment, socio-economics and other factors that influence the commercial viability of a process. In this thesis a methodology to achieve this objective is described. The completed methodology includes process chain generation, process modelling and subsequent analysis and comparison of results in order to evaluate alternative process routes. A modular structure was chosen to allow greater flexibility and allowing the user to generate a large number of different biorefinery configurations The significance of the approach is that the methodology is defined and is thus rigorous and consistent and may be readily re-examined if circumstances change. There was the requirement for consistency in structure and use, particularly for multiple analyses. It was important that analyses could be quickly and easily carried out to consider, for example, different scales, configurations and product portfolios and so that previous outcomes could be readily reconsidered. The result of the completed methodology is the identification of the most promising biorefinery chains from those considered as part of the European Biosynergy Project.

Practices and views on fetal heart monitoring:A structured observation and interview study

Objective: To assess and explain deviations from recommended practice in National Institute for Clinical Excellence (NICE) guidelines in relation to fetal heart monitoring. Design: Qualitative study. Setting: Large teaching hospital in the UK. Sample: Sixty-six hours of observation of 25 labours and interviews with 20 midwives of varying grades. Methods: Structured observations of labour and semistructured interviews with midwives. Interviews were undertaken using a prompt guide, audiotaped, and transcribed verbatim. Analysis was based on the constant comparative method, assisted by QSR N5 software. Main outcome measures: Deviations from recommended practice in relation to fetal monitoring and insights into why these occur. Results: All babies involved in the study were safely delivered, but 243 deviations from recommended practice in relation to NICE guidelines on fetal monitoring were identified, with the majority (80%) of these occurring in relation to documentation. Other deviations from recommended practice included indications for use of electronic fetal heart monitoring and conduct of fetal heart monitoring. There is evidence of difficulties with availability and maintenance of equipment, and some deficits in staff knowledge and skill. Differing orientations towards fetal monitoring were reported by midwives, which were likely to have impacts on practice. The initiation, management, and interpretation of fetal heart monitoring is complex and distributed across time, space, and professional boundaries, and practices in relation to fetal heart monitoring need to be understood within an organisational and social context. Conclusion: Some deviations from best practice guidelines may be rectified through straightforward interventions including improved systems for managing equipment and training. Other deviations from recommended practice need to be understood as the outcomes of complex processes that are likely to defy easy resolution. © RCOG 2006.

Strategic development process and complex adaptive systems

The two areas of theory upon which this research was based were „strategy development process?(SDP) and „complex adaptive systems? (CAS), as part of complexity theory, focused on human social organisations. The literature reviewed showed that there is a paucity of empirical work and theory in the overlap of the two areas, providing an opportunity for contributions to knowledge in each area of theory, and for practitioners. An inductive approach was adopted for this research, in an effort to discover new insights to the focus area of study. It was undertaken from within an interpretivist paradigm, and based on a novel conceptual framework. The organisationally intimate nature of the research topic, and the researcher?s circumstances required a research design that was both in-depth and long term. The result was a single, exploratory, case study, which included use of data from 44 in-depth, semi-structured interviews, from 36 people, involving all the top management team members and significant other staff members; observations, rumour and grapevine (ORG) data; and archive data, over a 5½ year period (2005 – 2010). Findings confirm the validity of the conceptual framework, and that complex adaptive systems theory has potential to extend strategy development process theory. It has shown how and why the strategy process developed in the case study organisation by providing deeper insights to the behaviour of the people, their backgrounds, and interactions. Broad predictions of the „latent strategy development? process and some elements of the strategy content are also possible. Based on this research, it is possible to extend the utility of the SDP model by including peoples? behavioural characteristics within the organisation, via complex adaptive systems theory. Further research is recommended to test limits of the application of the conceptual framework and improve its efficacy with more organisations across a variety of sectors.

Functional characterization of GABAergic pallidopallidal and striatopallidal synapses in the rat globus pallidus in vitro

As a central integrator of basal ganglia function, the external segment of the globus pallidus (GP) plays a critical role in the control of voluntary movement. Driven by intrinsic mechanisms and excitatory glutamatergic inputs from the subthalamic nucleus, GP neurons receive GABAergic inhibitory input from the striatum (Str-GP) and from local collaterals of neighbouring pallidal neurons (GP-GP). Here we provide electrophysiological evidence for functional differences between these two inhibitory inputs. The basic synaptic characteristics of GP-GP and Str-GP GABAergic synapses were studied using whole-cell recordings with paired-pulse and train stimulation protocols and variance-mean (VM) analysis. We found (i) IPSC kinetics are consistent with local collaterals innervating the soma and proximal dendrites of GP neurons whereas striatal inputs innervate more distal regions. (ii) Compared to GP-GP synapses Str-GP synapses have a greater paired-pulse ratio, indicative of a lower probability of release. This was confirmed using VM analysis. (iii) In response to 20 and 50 Hz train stimulation, GP-GP synapses are weakly facilitatory in 1 mm external calcium and depressant in 2.4 mm calcium. This is in contrast to Str-GP synapses which display facilitation under both conditions. This is the first quantitative study comparing the properties of GP-GP and Str-GP synapses. The results are consistent with the differential location of these inhibitory synapses and subtle differences in their release probability which underpin stable GP-GP responses and robust short-term facilitation of Str-GP responses. These fundamental differences may provide the physiological basis for functional specialization.

Information management and the holistic, process-oriented enterprise

This research examines the role of the information management process within a process-oriented enterprise, Xerox Ltd. The research approach is based on a post-positive paradigm and has resulted in thirty-five idiographic statements. The three major outcomes are: 1. The process-oriented holistic enterprise is an organisation that requires a long-term management commitment to its development. It depends on the careful management of people, tasks, information and technology. A complex integration of business processes is required and this can be managed through the use of consistent documentation techniques, clarity in the definition of process responsibilities and management attention to the global metrics and the centralisation of the management of the process model are critical to its success. 2. The role of the information management process within the context of a process-oriented enterprise is to provide flexible and cost-effective applications, technological, and process support to the business. This is best achieved through a centralisation of the management of information management and of the process model. A business-led approach combined with the consolidation of applications, information, process, and data architectures is central to providing effective business and process-focused support. 3. In a process oriented holistic enterprise, process and information management are inextricably linked. The model of process management depends heavily on information management, whilst the model of information management is totally focused around supporting and creating the process model. The two models are mutually creating - one cannot exist without the other. There is a duality concept of process and information management.