Task-Technology Fit and Employees’ Exploration of Enterprise Systems: Moderating Role of Local Management Commitment

Based on task-technology fit theory and adaptive structuration theory, we propose that employees’ exploration of enterprise systems is mainly influenced by three fundamental components: task, technology, and organizational environment. Accordingly, a research model is developed to interpret how task variety, system modularity, and local management commitment jointly affect employees’ system exploration. The model is tested with a survey of enterprise system users in six firms, and several meaningful findings are yielded. First, all of the three antecedents can directly affect system exploration. Second, task variety can positively moderate the effects of system modularity on system exploration. Third, local management commitment can strengthen the effects of system modularity and task variety on employees’ system exploration. The limitations and implications for research and practice are discussed

Implementation, context and complexity

Background - Context is a problem in research on health behaviour change, knowledge translation, practice implementation and health improvement. This is because many intervention and evaluation designs seek to eliminate contextual confounders, when these represent the normal conditions into which interventions must be integrated if they are to be workable in practice. Discussion - We present an ecological model of the ways that participants in implementation and health improvement processes interact with contexts. The paper addresses the problem of context as it affects processes of implementation, scaling up and diffusion of interventions. We extend our earlier work to develop Normalisation Process Theory and show how these processes involve interactions between mechanisms of resource mobilisation, collective action and negotiations with context. These mechanisms are adaptive. They contribute to self-organisation in complex adaptive systems. Conclusion - Implementation includes the translational efforts that take healthcare interventions beyond the closed systems of evaluation studies into the open systems of ‘real world’ contexts. The outcome of these processes depends on interactions and negotiations between their participants and contexts. In these negotiations, the plasticity of intervention components, the degree of participants’ discretion over resource mobilisation and actors’ contributions, and the elasticity of contexts, all play important parts. Understanding these processes in terms of feedback loops, adaptive mechanisms and the practical compromises that stem from them enables us to see the mechanisms specified by NPT as core elements of self-organisation in complex systems

Review of complex adaptive systems in nursing practice

This article describes the most typical characteristics of complex adaptive systems (CAS) theory and how it works in healthcare organizations and nursing practice. Complexity science belongs to newest systems thinking, which explore complex systems by focusing on the system components, relationships and interconnections rather than on the individual components themselves. The nurse must therefore always keep in mind the larger picture when caring for the individual patient and expect to be disturbed by unexpected possibilities. The incorporation of complexity science concepts into the practice of nursing leadership encourages new ways of thinking about organizations and is a natural model for the ideals and expected results of skilled nursing. CAS theory will take a permanent place in the healthcare organizations activities, improve nursing processes and create a better work environment for nursing and job satisfaction

Understanding performance measurement from a social systems perspective

This thesis was previously held under moratorium from 3 December 2019 to 3 December 2021.Performance measurement (PM) systems fail to predict organisational outcomes reliably because organisations face futures so inherently unknowable that it is impossible to comprehend the full range of potential outcomes open to them. Organisations are complex, adaptive, social systems whose distinctive activity is decision-making. They are heterogeneous entities whose capabilities, behaviours, and circumstances are unique, emerging from their histories and previous decisions. Organisational reality is a social construct delivered through practice. This thesis investigates whether considering PM from a social systems perspective improves PM’s effectiveness. The argument made is organisations connect through social systems and operate through practice with people, processes, and their interactions fundamental to how they perform. A middle-range management theory is presented aimed at making organisations the best they can be with the resources available to them and in the economic circumstances they find themselves. It does this by understanding and reconfiguring the organisation’s social system using a structured approach to optimise business processes and performance measures based on a combination of emergent behaviour and practice. Given the reality of radical uncertainty the focus is not on predicting outcomes but on uncovering the explanatory mechanisms behind events caused by specific managed improvement interventions. Understanding the behaviour of dynamically interacting components is done using realist evaluation based on social interactions, emergent powers and social intervention mechanisms. This approach changed behaviours and performance outcomes in case study organisations. The use of an ‘inside-out’ social systems perspective, coupled to critical realism with its focus on explanation, enabled the causal relationships of importance to be identified and the performance ‘black box’ to be opened up. This research contributes to closing the PMM theory-practice gap by proposing the performance focus needs to be on the social system rather than the measures, that is, on the ‘means’ rather than the ‘ends’. It also offers a competing theoretical framework to organisational control theory for PMM, one grounded in social systems and practice theory. The social systems perspective is not considered specific to PM and potentially can be applied to all other business processesPerformance measurement (PM) systems fail to predict organisational outcomes reliably because organisations face futures so inherently unknowable that it is impossible to comprehend the full range of potential outcomes open to them. Organisations are complex, adaptive, social systems whose distinctive activity is decision-making. They are heterogeneous entities whose capabilities, behaviours, and circumstances are unique, emerging from their histories and previous decisions. Organisational reality is a social construct delivered through practice. This thesis investigates whether considering PM from a social systems perspective improves PM’s effectiveness. The argument made is organisations connect through social systems and operate through practice with people, processes, and their interactions fundamental to how they perform. A middle-range management theory is presented aimed at making organisations the best they can be with the resources available to them and in the economic circumstances they find themselves. It does this by understanding and reconfiguring the organisation’s social system using a structured approach to optimise business processes and performance measures based on a combination of emergent behaviour and practice. Given the reality of radical uncertainty the focus is not on predicting outcomes but on uncovering the explanatory mechanisms behind events caused by specific managed improvement interventions. Understanding the behaviour of dynamically interacting components is done using realist evaluation based on social interactions, emergent powers and social intervention mechanisms. This approach changed behaviours and performance outcomes in case study organisations. The use of an ‘inside-out’ social systems perspective, coupled to critical realism with its focus on explanation, enabled the causal relationships of importance to be identified and the performance ‘black box’ to be opened up. This research contributes to closing the PMM theory-practice gap by proposing the performance focus needs to be on the social system rather than the measures, that is, on the ‘means’ rather than the ‘ends’. It also offers a competing theoretical framework to organisational control theory for PMM, one grounded in social systems and practice theory. The social systems perspective is not considered specific to PM and potentially can be applied to all other business processe

From Projection Pursuit and CART to Adaptive Discriminant Analysis

Abstract—While many efforts have been put into the development of nonlinear approximation theory and its applications to signal and image compression, encoding and denoising, there seems to be very few theoretical developments of adaptive discriminant representations in the area of feature extraction, selection and signal classification. In this paper, we try to advocate the idea that such developments and efforts are worthwhile, based on the theorerical study of a data-driven discriminant analysis method on a simple—yet instructive—example. We consider the problem of classifying a signal drawn from a mixture of two classes, using its projections onto low-dimensional subspaces. Unlike the linear discriminant analysis (LDA) strategy, which selects subspaces that do not depend on the observed signal, we consider an adaptive sequential selection of projections, in the spirit of nonlinear approximation and classification and regression trees (CART): at each step, the subspace is enlarged in a direction that maximizes the mutual information with the unknown class. We derive explicit characterizations of this adaptive discriminant analysis (ADA) strategy in two situations. When the two classes are Gaussian with the same covariance matrix but different means, the adaptive subspaces are actually nonadaptive and can be computed with an algorithm similar to orthonormal matching pursuit. When the classes are centered Gaussians with different covariances, the adaptive subspaces are spanned by eigen-vectors of an operator given by the covariance matrices (just as could be predicted by regular LDA), however we prove that the order of observation of the components along these eigen-vectors actually depends on the observed signal. Numerical experiments on synthetic data illustrate how data-dependent features can be used to outperform LDA on a classification task, and we discuss how our results could be applied in practice. Index Terms—Classification and regression trees (CART), classification tree, discriminant analysis, mutual information, nonlinear approximation, projection pursuit, sequential testing. I

Toward a script theory of guidance in computer-supported collaborative learning

This article presents an outline of a script theory of guidance for computer-supported collaborative learning (CSCL). With its four types of components of internal and external scripts (play, scene, role, and scriptlet) and seven principles, this theory addresses the question how CSCL practices are shaped by dynamically re-configured internal collaboration scripts of the participating learners. Furthermore, it explains how internal collaboration scripts develop through participation in CSCL practices. It emphasizes the importance of active application of subject matter knowledge in CSCL practices, and it prioritizes transactive over non-transactive forms of knowledge application in order to facilitate learning. Further, the theory explains how external collaboration scripts modify CSCL practices and how they influence the development of internal collaboration scripts. The principles specify an optimal scaffolding level for external collaboration scripts and allow for the formulation of hypotheses about the fading of external collaboration scripts. Finally, the article points towards conceptual challenges and future research questions

Toward a Theory of Learner-Centered Training Design: An Integrative Framework of Active Learning

[Excerpt] The goal of this chapter, therefore, is to develop an integrative conceptual framework of active learning, and we do this by focusing on three primary issues. First, we define the active learning approach and contrast it to more traditional, passive instructional approaches. We argue that the active learning approach can be distinguished from not only more passive approaches to instruction but also other forms of experiential learning based on its use of formal training components to systematically influence trainees\u27 cognitive, motivational, and emotion self-regulatory processes. Second, we examine how specific training components can be used to influence each of these process domains. Through a review of prior research, we extract core training components that cut across different active learning interventions, map these components onto specific process domains, and consider the role of individual differences in shaping the effects of these components (aptitude-treatment interactions [ATIs]). A final issue examined in this chapter concerns the outcomes associated with the active learning approach. Despite its considerable versatility, the active learning approach is not the most efficient or effective means of responding to all training needs. Thus, we discuss the impact of the active learning approach on different types of learning outcomes in order to identify the situations under which it is likely to demonstrate the greatest utility. We conclude the chapter by highlighting research and practical implications of our integrated framework, and we outline an agenda for future research on active learning