“Filling out the forms was a nightmare” : project evaluation and the reflective practitioner in community theatre in contemporary Northern Ireland

Since the Good Friday Agreement of 1998, large sums have been invested in community theatre projects in Northern Ireland, in the interests of conflict transformation and peace building. While this injection of funds has resulted in an unprecedented level of applied theatre activity, opportunities to maximise learning from this activity are being missed. It is generally assumed that project evaluation is undertaken at least partly to assess the degree of success of projects against important social objectives, with a view to learning what works, what does not, and what might work in the future. However, three ethnographic case studies of organisations delivering applied theatre projects in Northern Ireland indicate that current processes used to evaluate such projects are both flawed and inadequate for this purpose. Practitioners report that the administrative work involved in applying for and justifying funding is onerous, burdensome, and occurs at the expense of artistic activity. This is a very real concern when the time and effort devoted to ‘filling out the forms’ does not ultimately result in useful evaluative information. There are strong disincentives for organisations to report honestly on their experiences of difficulties, or undesirable impacts of projects, and this problem is not transcended by the use of external evaluators. Current evaluation processes provide little opportunity to capture unexpected benefits of projects, and small but significant successes which occur in the context of over-ambitious objectives. Little or no attempt is made to assess long-term impacts of projects on communities. Finally, official evaluation mechanisms fail to capture the reflective practice and dialogic analysis of practitioners, which would richly inform future projects. The authors argue that there is a need for clearer lines of communication, and more opportunities for mutual learning, among stakeholders involved in community development. In particular, greater involvement of the higher education sector in partnership with government and non-government agencies could yield significant benefits in terms of optimizing learning from applied theatre project evaluations.

Evolution and change in industrial clusters : an analysis of Hsinchu and Sophia Antipolis

The aim of this paper is to advance understandings of the processes of cluster-building and evolution, or transformative and adaptive change, through the conscious design and reflective activities of private and public actors. A model of transformation is developed which illustrates the importance of actors becoming exposed to new ideas and visions for industrial change by political entrepreneurs and external networks. Further, actors must be guided in their decision-making and action by the new vision, and this requires that they are persuaded of its viability through the provision of test cases and supportive resources and institutions. In order for new ideas to become guiding models, actors must be convinced of their desirability through the portrayal of models as a means of confronting competitive challenges and serving the economic interests of the city/region. Subsequent adaptive change is iterative and reflexive, involving a process of strategic learning amongst key industrial and political actors.

How Novices Model Business Processes

In this paper, we examine the design of business process diagrams in contexts where novice analysts only have basic design tools such as paper and pencils available, and little to no understanding of formalized modeling approaches. Based on a quasi-experimental study with 89 BPM students, we identify five distinct process design archetypes ranging from textual to hybrid, and graphical representation forms. We also examine the quality of the designs and identify which representation formats enable an analyst to articulate business rules, states, events, activities, temporal and geospatial information in a process model. We found that the quality of the process designs decreases with the increased use of graphics and that hybrid designs featuring appropriate text labels and abstract graphical forms are well-suited to describe business processes. Our research has implications for practical process design work in industry as well as for academic curricula on process design.

Sourcing business and software services

With the advancement of Service-Oriented Architecture in the technical and business domain, the management & engineering of services requires a thorough and systematic understanding of the service lifecycle for both business and software services. However, while service-oriented approaches acknowledge the importance of the service ecosystem, service lifecycle models are typically internally focused, paying limited attention to processes related to offering services to or using services from other actors. In this paper, we address this need by discussing the relations between a comprehensive service lifecycle approach for service management & engineering and the sourcing & purchasing of services. In particular we pay attention to the similarities and differences between sourcing business and software services, the alignment between service management & engineering and sourcing & purchasing, the role of sourcing in the transformation of an organization towards a service-oriented paradigm, the role of architectural approaches to sourcing in this transformation, and the sourcing of specific services at different levels of granularity.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.