Francesco Danzi, Giacomo Frulla and Giulio Romeo
This paper aims to present a systematic performance-oriented procedure to predict structural responses of composite layered structures. The procedure has a direct application in…
Abstract
Purpose
This paper aims to present a systematic performance-oriented procedure to predict structural responses of composite layered structures. The procedure has a direct application in the preliminary design of aerospace composite structures evaluating the right and most effective material.
Design/methodology/approach
The aforementioned procedure is based upon the definition of stiffness invariants. In the paper, the authors briefly recall the definition and the physical explanation of the invariants, i.e. the trace; then they present the scaling procedure for the selection of the best material for a fixed geometrical shape.
Findings
The authors report the basic principles of the scaling procedure and several examples pertaining typical responses sought in the preliminary design of aeronautic structures
Research limitations/implications
Typically, during early stages, engineers had to perform the daunting task of balancing among functional requirements and constraints and give the optimum solution in terms of structural concept and material selection. Moreover, preliminary design activities require evaluating different responses as a function of as less as possible parameters, ensuring medium to high fidelity. The importance of incorporating as much physics and understanding of the problem as early as possible in the preliminary design stages is therefore fundamental. A robust and systematic procedure is necessary.
Practical implications
The time/effort reduction in the preliminary design of composite structures can increase the overall quality of the configuration chosen.
Social implications
Reduction in design costs and time.
Originality/value
In spite of the well-known invariant properties of composites, the application and extension to the preliminary design of composite structures by means of a scaling rule is new and original.
Details
Keywords
Ylenia Cavacece, Giulio Maggiore, Riccardo Resciniti and Andrea Moretta Tartaglione
The purpose of this paper is to investigate user satisfaction with digital health solutions by identifying and prioritizing different service attributes on the basis of their…
Abstract
Purpose
The purpose of this paper is to investigate user satisfaction with digital health solutions by identifying and prioritizing different service attributes on the basis of their impact on improving user satisfaction.
Design/methodology/approach
Through a literature review and interviews with health professionals and patients, 20 attributes of digital health services provided in Italy have been identified. User satisfaction with these attributes has been evaluated by adopting the Kano model’s continuous and discrete analyses.
Findings
The findings reveal the essential attributes of digital health services that meet users' expectations, identify the attributes that users appreciate or dislike having and highlight unexpected attributes that lead to a significant boost in satisfaction when provided.
Research limitations/implications
This study demonstrates the efficacy of the Kano model in assessing the nonlinear correlation between user satisfaction and the quality of digital health services, thus contributing to fill a gap in the literature in this area. The main limitation of this work is the use of a non-probabilistic sampling method.
Practical implications
This research suggests healthcare institutions and organizations consider user preferences when designing digital health solutions to increase their satisfaction. The results indicate different effects on user satisfaction and dissatisfaction for different categories of attributes in the Italian context.
Originality/value
Previous works studied customer satisfaction with digital health, assuming a linear relationship with service quality, or investigated consumer adoption intentions focusing on the technological factors. This work advances available knowledge by analyzing the nonlinear relationship between digital health attributes and users’ satisfaction and dissatisfaction.
Details
Keywords
Isabelle Latham, Dawn Brooker and Kay de Vries
This paper describes a model of “Learning to care” derived from a study exploring how care workers in care homes learn to care for people living with dementia. The “Learning to…
Abstract
Purpose
This paper describes a model of “Learning to care” derived from a study exploring how care workers in care homes learn to care for people living with dementia. The “Learning to care” model is primarily informal in nature in which influences such as formalised training and organisational culture impact care outcomes indirectly rather than directly.
Design/methodology/approach
This study used a focused, critical ethnographic approach in two care homes in England resulting in 63 h of observation of care of people living with advanced dementia, 15 semi-structured interviews and 90 in-situ ethnographic interviews with care staff.
Findings
The findings reveal a three-level model of learning to care. At the level of day-to-day interactions is a mechanism for learning that is wholly informal and follows the maxim “What Works is What Matters”. Workers draw on resources and information within this process derived from their personal experiences, resident influences and care home cultural knowledge. Cultural knowledge is created through a worker’s interactions with colleagues and the training they receive, meaning that these organisational level influences affect care practice only indirectly via the “What Works is What Matters” mechanism.
Originality/value
This study makes an original contribution by explaining the nature of day-to-day informal learning processes as experienced by care workers and those living with dementia in care homes. In particular, it illuminates the specific mechanisms by which organisational culture has an effect on care practice and the limitations of formal training in influencing such practice.