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This paper draws on a telephone survey of 116 independent SMEs to explore the impact of a variety of training interventions on human resource (HR) practices and business performance in Great Britain. The paper investigates the extent to which targeting such interventions on the managers of SMEs affects the impact and the likelihood of changes in HR practices but finds no statistically significant relationship. The research findings suggest that whilst training interventions have positively contributed to the establishment of HR practices and are perceived by SME managers to have met the needs of the organisation, their impact on a range of business performance indicators is fairly modest. Furthermore the research identifies the propensity of SMEs who are currently engaged in training to become involved in these interventions whilst the majority of SMEs who are not engaged in external training activities remain untouched by the policy intervention.

The purpose of this paper is to explore the drivers, inhibitors and enablers of creating a textile-to-textile recycling system in the Scandinavian fashion industry. It investigates the technology, innovation and systemic changes required to enable circular supply chains.

The research study uses a qualitative, interpretivist approach, drawing on in-depth semi-structured interviews with stakeholders in the Scandinavian fashion industry.

The main inhibitors to textile-to-textile recycling systems in the Scandinavian fashion industry are: limited technology which creates a challenge for separating materials; high costs of research and development and building the supporting logistics; complexity of supply chains including the multitude of stakeholders involved in product development. The enablers are design and use of new materials, increased garment collection and collaboration. This research suggests that sorting and recycling technology can be enhanced with the use of digital technologies, as this would create transparency, traceability and automatisation.

The research is limited by a small sample size and lack of representation of all key stakeholder groups, which limits the ability to generalise these findings. However, as an exploratory study, the findings provide insights that can be further tested in other contexts.

Understanding of textile-to-textile recycling is emerging both theoretically and practically, however, there is still much that is not understood. This research contributes to furthering understanding of how technology, collaboration and systemic change in the fashion industry can support opportunities for textile-to-textile recycling, thereby aligning with circular economy principles.

This research models the impact of patient perceptions of care quality on overall patient satisfaction in a rural healthcare organization over a three-year time period. The purpose of this paper is to determine if the factors that influence perceptions of service quality change over time and if the change affects overall patient satisfaction.

Data were collected for three fiscal years (2012-2014) using a 36-question, Likert-scaled attitudinal survey. Multiple regression analysis was performed to identify which constructs of five different service quality dimensions were statistically significant in predicting overall patient satisfaction. Paired comparison of means and ANOVA F-tests highlighted significant differences across years and demographics.

Multiple regression models of overall patient satisfaction over a three-year time period had significant repeat variables, indicating salience of the dimensions and constructs of service quality that predict patient satisfaction. However, some dimensions of service quality did not remain significant from one year to another, indicating there may be a gap in the patient service cycle over an extended time frame.

This paper explored the sequential relationship between patient satisfaction survey data and perceptions of service quality over a multi-year time frame. The research focussed on outpatient medical clinics, while the majority of previous studies have focussed on acute care or inpatient stays. A longitudinal study is especially relevant for outpatient clinics where continuity of care is important.

In this paper we report on a theoretical model of structured document indexing and retrieval based on the Dempster‐Shafer Theory of Evidence. This includes a description of our model of structured document retrieval, the representation of structured documents, the representation of individual components, how components are combined, details of the combination process, and how relevance is captured within the model. We also present a detailed account of an implementation of the model, and an evaluation scheme designed to test the effectiveness of our model. Finally we report on the details and results of a series of experiments performed to investigate the characteristics of the model.

Workforce development is becoming a higher priority for government, both as a means of addressing social exclusion and raising competitiveness. However there is limited evidence of the contribution of training to the success of individual firms and even less evidence of the impact of such training activity on small to medium‐sized enterprise (SME) employees. This paper draws on a survey of 1,000 employees to investigate the impact of a training intervention on employees in SME workplaces. It explores issues associated with the equity of provision of training in the workplace and the impact of training on the employability of SME employees in the labour market. The results suggest that training interventions lead to positive outcomes for the majority of SME employees, particularly those working in organisations with relatively formalised training practices. It concludes by suggesting that there should be a greater focus on the employee dimension in research and policy regarding training in SMEs.

Although the Social Progress Index offers a thorough overview of the top-ranked countries with a highly developed social performance, it assigns the same weight to all component scores, implying that each component has identical and independent contribution to the SPI. By removing these flawed assumptions, the purpose of this paper is to examine the causal relationships among component scores and identify the critical components for reform priorities.

The authors propose an alternative approach to exploring the causal relationships and prioritizing the underlying components of the SPI. The four-step methodology comprises cluster analysis, data mining, partial least square path modeling, and importance-performance matrix analysis.

The authors find evidence of causal interrelations between the 12 components of the SPI. To accelerate social progress, the authors suggest that policy makers should allocate resources in order of priority to personal freedom and choice, personal rights, access to advanced education, water and sanitation, access to information and communications, tolerance and inclusion, personal safety, shelter, ecosystem sustainability, nutrition and basic medical care, health and wellness, and, finally, access to basic knowledge.

Policy makers in government, business, and civil society should become aware of causal relationships among the 12 components of the SPI and select an appropriate methodology to prioritize areas where social improvement is most needed.

Allowing for unequal weighting and causal relationships between component scores of the SPI, the authors’ methodology is the first attempt to offer a concrete way to identify which areas of social progress should constitute priorities for policy reforms.

This paper aims to dynamically analyze the opportunities and challenges of AI in the defense sector in Lebanon or any security agency or any organization with sensitive data through a resource-based view perspective, the adoption of artificial intelligence (AI)/narrow AI applications in the Lebanese Armed Forces (LAF) and to diagnose the current strategic orientation toward innovation and technology within the LAF while avoiding isomorphism.

The methodology is based on a qualitative interpretive case-study approach collected from several departments of the LAF. In fact, there is a developing convention to use qualitative research approaches among which case studies to study information technology phenomena (Trauth and Jessup, 2000; Benbasat et al., 1987; Klein and Meyers, 1999). Data were collected through centered semi-structured in-depth interviews (two to three hours each) with an interview guide coded abductively between the researchers and the interviewees conducted in numerous departments of the LAF with their top officials and generals (O1, O2, O3…); the anonymity of the interviewees was kept due to the sensitivity of the data collected, which took place between September 2018 and March 2019. Data consolidation and processing were conducted using NVivo.

This paper shows that the LAF is undeniably facing many challenges among which isomorphism caused by the lack of resources; it also shows that narrow AI applications provide new avenues for the LAF to avoid such institutional isomorphism.

The role of narrow AI in limiting isomorphism in the defense sector.

Healthcare facilities are entering an era of increased oversight and heightened expectations concerning both reduced costs and measureable quality. The US Affordable Care Act requires healthcare organizations to collect certain metrics, including patient assessments of quality, in order to monitor and improve the quality of healthcare. These metrics are used as a basis for graduated insurance reimbursements, and are available to consumers as an aid in selecting healthcare providers and insurance plans. The purpose of this paper is to provide healthcare providers with the analytic capabilities to better understand quality of care from the patient’s point of view.

This research examines patient satisfaction data from a multi-specialty Medical Practice Group, and uses regression analysis and paired comparisons to provide insight into patient perceptions of care quality.

Results show that variables related to Access, Moving Through the Visit, Nurse/Assistant, Care Provider and Personal Issues significantly impact overall assessments of care quality. In addition, while gender and type of care provider do not appear to have an impact on overall patient satisfaction, significant differences do exist based on age group, specialty of the physician and clinic type.

This study differs from most academic research as it focusses on medical practices, rather than hospitals, and includes multiple clinic types, medical specialties and physician types in the analysis. The study demonstrates how analytics and patient perceptions of quality can inform policy decisions.

The prerequisite for most traditional visual simultaneous localization and mapping (V-SLAM) algorithms is that most objects in the environment should be static or in low-speed locomotion. These algorithms rely on geometric information of the environment and restrict the application scenarios with dynamic objects. Semantic segmentation can be used to extract deep features from images to identify dynamic objects in the real world. Therefore, V-SLAM fused with semantic information can reduce the influence from dynamic objects and achieve higher accuracy. This paper aims to present a new semantic stereo V-SLAM method toward outdoor dynamic environments for more accurate pose estimation.

First, the Deeplabv3+ semantic segmentation model is adopted to recognize semantic information about dynamic objects in the outdoor scenes. Second, an approach that combines prior knowledge to determine the dynamic hierarchy of moveable objects is proposed, which depends on the pixel movement between frames. Finally, a semantic stereo V-SLAM based on ORB-SLAM2 to calculate accurate trajectory in dynamic environments is presented, which selects corresponding feature points on static regions and eliminates useless feature points on dynamic regions.

The proposed method is successfully verified on the public data set KITTI and ZED2 self-collected data set in the real world. The proposed V-SLAM system can extract the semantic information and track feature points steadily in dynamic environments. Absolute pose error and relative pose error are used to evaluate the feasibility of the proposed method. Experimental results show significant improvements in root mean square error and standard deviation error on both the KITTI data set and an unmanned aerial vehicle. That indicates this method can be effectively applied to outdoor environments.

The main contribution of this study is that a new semantic stereo V-SLAM method is proposed with greater robustness and stability, which reduces the impact of moving objects in dynamic scenes.

The purpose of this paper is to analyse relations between geographical and competence proximity and development of cooperation in cluster initiatives.

The research was based on an original theoretical concept referring to the trajectory of the development of cooperative relations in cluster initiatives. The research was carried out in mid-2017, in four purposefully selected cluster initiatives. The research sample was 132 cluster enterprises. The main research strategy involved non-experimental models; the basic method of data collection was an online questionnaire.

The results indicated that the role of geographical and competence proximity depends on the level of cooperation in a cluster initiative. In both these dimensions, proximity was important during the initial stage of cluster development: to start cooperation between the members, however, when more mature forms of cooperation were undertaken, the factor of common location was not so crucial any longer. It was also recommended to maintain some competence distance between the partners.

The main limitations referred to the static character of the data, the use of original measurement tools, which had not been tested before, the small and little differentiated research sample and the subjective nature of the research. The above-mentioned limitations should be viewed as a starting point for further empirical research.

Knowledge on the significance of geographical and competence proximity at various levels of cooperation in clusters is valuable for efficient management of a cluster and for higher competitiveness that it can achieve.

The research study contributes to the literature, which refers to the question of proximity in clusters through the analysis of relations between geographical and competence proximity and development of cooperation in cluster initiatives. The results of the research point out that the role of geographical and competence proximity evolves with the development of cooperation in cluster initiatives.