IS-implementation: a tri-motors theory of organizational change. Case study of how an IT-enabled process of organizational change because of the presence of a teleological, life-cycle, and dialectical motor unfolds within a Dutch government organization.
Spicer, David P.
KeywordIT-enabled organizational change
Tri-motors ideal-type process theory
The University of Bradford theses are licenced under a Creative Commons Licence.
InstitutionUniversity of Bradford
DepartmentSchool of Management
MetadataShow full item record
AbstractThe reason for the study is that IT-enabled organizational change processes such as information system implementations have high costs and disappointing results. Studies to identify causes of the mentioned failures are mainly based on a variance approach. This study applies another approach which is not yet performed in this field of research and affects several themes. Based on a process approach data is compared with ideal-process theories to identify the generative mechanisms causing the unfolding of the process. Thus, the study identifies a recipe and not the ingredients.
Showing items related by title, author, creator and subject.
Effect before cause: supramodal recalibration of sensorimotor timingHeron, James; Hanson, James Vincent Michael; Whitaker, David J. (2009)Our motor actions normally generate sensory events, but how do we know which events were self generated and which have external causes? Here we use temporal adaptation to investigate the processing stage and generality of our sensorimotor timing estimates. Methodology/Principal Findings: Adaptation to artificially-induced delays between action and event can produce a startling percept¿upon removal of the delay it feels as if the sensory event precedes its causative action. This temporal recalibration of action and event occurs in a quantitatively similar manner across the sensory modalities. Critically, it is robust to the replacement of one sense during the adaptation phase with another sense during the test judgment. Conclusions/Significance: Our findings suggest a high-level, supramodal recalibration mechanism. The effects are well described by a simple model which attempts to preserve the expected synchrony between action and event, but only when causality indicates it is reasonable to do so. We further demonstrate that this model successfully characterises related adaptation data from outside the sensorimotor domain.
Disruptions to human speed perception induced by motion adaptation and transcranial magnetic stimulation.Burton, Mark P.; McKeefry, Declan J.; Barrett, Brendan T.; Vakrou, Chara; Morland, A.B. (Wiley, 2009-11)To investigate the underlying nature of the effects of transcranial magnetic stimulation (TMS) on speed perception, we applied repetitive TMS (rTMS) to human V5/MT+ following adaptation to either fast- (20 deg/s) or slow (4 deg/s)-moving grating stimuli. The adapting stimuli induced changes in the perceived speed of a standard reference stimulus moving at 10 deg/s. In the absence of rTMS, adaptation to the slower stimulus led to an increase in perceived speed of the reference, whilst adaptation to the faster stimulus produced a reduction in perceived speed. These induced changes in speed perception can be modelled by a ratio-taking operation of the outputs of two temporally tuned mechanisms that decay exponentially over time. When rTMS was applied to V5/MT+ following adaptation, the perceived speed of the reference stimulus was reduced, irrespective of whether adaptation had been to the faster- or slower-moving stimulus. The fact that rTMS after adaptation always reduces perceived speed, independent of which temporal mechanism has undergone adaptation, suggests that rTMS does not selectively facilitate activity of adapted neurons but instead leads to suppression of neural function. The results highlight the fact that potentially different effects are generated by TMS on adapted neuronal populations depending upon whether or not they are responding to visual stimuli.
Current Based Fault Detection and Diagnosis of Induction Motors. Adaptive Mixed-Residual Approach for Fault Detection and Diagnosis of Rotor, Stator, Bearing and Air-Gap Faults in Induction Motors Using a Fuzzy Logic Classifier with Voltage and Current Measurement only.Ebrahimi, Kambiz M.; Wood, Alastair S.; Pestell, Charles; Bradley, William J. (University of BradfordSchool of Engineering, Design and Technology, 2015-06-16)Induction motors (IM) find widespread use in modern industry and for this reason they have been subject to a significant amount of research interest in recent times. One particular aspect of this research is the fault detection and diagnosis (FDD) of induction motors for use in a condition based maintenance (CBM) strategy; by effectively tracking the condition of the motor, maintenance action need only be carried out when necessary. This type of maintenance strategy minimises maintenance costs and unplanned downtime. The benefits of an effective FDD for IM is clear and there have been numerous studies in this area but few which consider the problem in a practical sense with the aim of developing a single system that can be used to monitor motor condition under a range of different conditions, with different motor specifications and loads. This thesis aims to address some of these problems by developing a general FDD system for induction motor. The solution of this problem involved the development and testing of a new approach; the adaptive mixed-residual approach (AMRA). The main aim of the AMRA system is to avoid the vast majority of unplanned failures of the machine and therefore as opposed to tackling a single induction motor fault, the system is developed to detect all four of the most statistically prevalent induction motor fault types; rotor fault, stator fault, air-gap fault and bearing fault. The mixed-residual fault detection algorithm is used to detect these fault types which includes a combination of spectral and model-based techniques coupled with particle swarm optimisation (PSO) for automatic identification of motor parameters. The AMRA residuals are analysed by a fuzzy-logic classifier and the system requires only current and voltage inputs to operate. Validation results indicate that the system performs well under a range of load torques and different coupling methods proving it to have significant potential for use in industrial applications.