Methodological implications of critical realism for mixed-methods research

Building on recent developments in mixed methods, we discuss the methodological implications of critical realism and explore how these can guide dynamic mixed-methods research design in information systems. Specifically, we examine the core ontological assumptions of CR in order to gain some perspective on key epistemological issues such as causation and validity, and illustrate how these shape our logic of inference in the research process through what is known as retroduction. We demonstrate the value of a CR-led mixed-methods research approach by drawing on a study that examines the impact of ICT adoption in the financial services sector. In doing so, we provide insight into the interplay between qualitative and quantitative methods and the particular value of applying mixed methods guided by CR methodological principles. Our positioning of demi-regularities within the process of retroduction contributes a distinctive development in this regard. We argue that such a research design enables us to better address issues of validity and the development of more robust meta-inferences.

Leadership of healthcare commissioning networks in England: a mixed-methods study on clinical commissioning groups.

To explore the relational challenges for general practitioner (GP) leaders setting up new network-centric commissioning organisations in the recent health policy reform in England, we use innovation network theory to identify key network leadership practices that facilitate healthcare innovation.

Complementary Phone Error training

This paper introduces a novel method for the training of a complementary acoustic model with respect to set of given acoustic models. The method is based upon an extension of the Minimum Phone Error (MPE) criterion and aims at producing a model that makes complementary phone errors to those already trained. The technique is therefore called Complementary Phone Error (CPE) training. The method is evaluated using an Arabic large vocabulary continuous speech recognition task. Reductions in word error rate (WER) after combination with a CPE-trained system were obtained with up to 0.7% absolute for a system trained on 172 hours of acoustic data and up to 0.2% absolute for the final system trained on nearly 2000 hours of Arabic data.

Training and assignment of multi-skilled workers for implementing seru production systems

Confronted with high variety and low volume market demands, many companies, especially the Japanese electronics manufacturing companies, have reconfigured their conveyor assembly lines and adopted seru production systems. Seru production system is a new type of work-cell-based manufacturing system. A lot of successful practices and experience show that seru production system can gain considerable flexibility of job shop and high efficiency of conveyor assembly line. In implementing seru production, the multi-skilled worker is the most important precondition, and some issues about multi-skilled workers are central and foremost. In this paper, we investigate the training and assignment problem of workers when a conveyor assembly line is entirely reconfigured into several serus. We formulate a mathematical model with double objectives which aim to minimize the total training cost and to balance the total processing times among multi-skilled workers in each seru. To obtain the satisfied task-to-worker training plan and worker-to-seru assignment plan, a three-stage heuristic algorithm with nine steps is developed to solve this mathematical model. Then, several computational cases are taken and computed by MATLAB programming. The computation and analysis results validate the performances of the proposed mathematical model and heuristic algorithm. © 2013 Springer-Verlag London.

Motor learning of novel dynamics is not represented in a single global coordinate system: evaluation of mixed coordinate representations and local learning.

Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

Rao-Blackwellized particle smoothers for mixed linear/nonlinear state-space models

We consider the smoothing problem for a class of conditionally linear Gaussian state-space (CLGSS) models, referred to as mixed linear/nonlinear models. In contrast to the better studied hierarchical CLGSS models, these allow for an intricate cross dependence between the linear and the nonlinear parts of the state vector. We derive a Rao-Blackwellized particle smoother (RBPS) for this model class by exploiting its tractable substructure. The smoother is of the forward filtering/backward simulation type. A key feature of the proposed method is that, unlike existing RBPS for this model class, the linear part of the state vector is marginalized out in both the forward direction and in the backward direction. © 2013 IEEE.

Structural tunability and switchable exciton emission in inorganic-organic hybrids with mixed halides

Room-temperature tunable excitonic photoluminescence is demonstrated in alloy-tuned layered Inorganic-Organic (IO) hybrids, (C12H 25NH3)2PbI4(1-y)Br4y (y = 0 to 1). These perovskite IO hybrids adopt structures with alternating stacks of low-dimensional inorganic and organic layers, considered to be naturally self-assembled multiple quantum wells. These systems resemble stacked monolayer 2D semiconductors since no interlayer coupling exists. Thin films of IO hybrids exhibit sharp and strong photoluminescence (PL) at room-temperature due to stable excitons formed within the low-dimensional inorganic layers. Systematic variation in the observed exciton PL from 510 nm to 350 nm as the alloy composition is changed, is attributed to the structural readjustment of crystal packing upon increase of the Br content in the Pb-I inorganic network. The energy separation between exciton absorption and PL is attributed to the modified exciton density of states and diffusion of excitons from relatively higher energy states corresponding to bromine rich sites towards the lower energy iodine sites. Apart from compositional fluctuations, these excitons show remarkable reversible flips at temperature-induced phase transitions. All the results are successfully correlated with thermal and structural studies. Such structural engineering flexibility in these hybrids allows selective tuning of desirable exciton properties within suitable operating temperature ranges. Such wide-range PL tunability and reversible exciton switching in these novel IO hybrids paves the way to potential applications in new generation of optoelectronic devices. © 2013 AIP Publishing LLC.