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The purpose of this research is to provide a theoretical framework for complex equipment quality risk evaluation. The primary aim of the framework is to enhance the ability to identify risks and improve risk control efficiency during the development phase.

A novel framework for quality risk evaluation in complex equipment is proposed, which integrates probabilistic hesitant fuzzy set-quality function deployment (PHFS-QFD) and grey clustering. PHFS-QFD is applied to identify the quality risk factors, and grey clustering is used to evaluate quality risks in cases of poor quality information during the development stage. The unfolding function of QFD is applied to simplify complex evaluation problems.

The methodology presents an innovative approach to quality risk evaluation for complex equipment development. The case analysis demonstrates that this method can efficiently evaluate the quality risks for aircraft development and systematically trace back the risk factors through hierarchical relationships. In comparison to traditional failure mode and effects analysis methods for quality risk assessment, this approach exhibits superior effectiveness and reliability in managing quality risks for complex equipment development.

This study contributes to the field by introducing a novel theoretical framework that combines PHFS-QFD and grey clustering. The integration of these approaches significantly improves the quality risk evaluation process for complex equipment development, overcoming challenges related to data scarcity and simplifying the assessment of intricate systems.

Currently, countries worldwide are struggling with the virus COVID-19 and the severe outbreak it brings. To better benefit from open government health data in the fight against this pandemic, this study developed a framework for assessing open government health data at the dataset level, providing a tool to evaluate current open government health data's quality and usability COVID-19.

Based on the review of the existing quality evaluation methods of open government data, the evaluation metrics and their weights were determined by 15 experts in health through the Delphi method and analytic hierarchy process. The authors tested the framework's applicability using open government health data related to COVID-19 in the US, EU and China.

The results of the test capture the quality difference of the current open government health data. At present, the open government health data in the US, EU and China lacks the necessary metadata. Besides, the number, richness of content and timeliness of open datasets need to be improved.

Unlike the existing open government data quality measurement, this study proposes a more targeted open government data quality evaluation framework that measures open government health data quality on a range of data quality dimensions with a fine-grained measurement approach. This provides a tool for accurate assessment of public health data for correct decision-making and assessment during a pandemic.

The aim of this study is to show that it is not necessary to use one of the current models of quality management. Self‐evaluation is to be considered as an essential practice for further education providers willing to improve their quality. The study aims to propose a quality framework with field‐related criteria.

The quality framework was developed on the base of a comparative model analysis. Its suitability was confirmed after an investigation with experts in further education.

It is possible to use the same criteria by implementing different models.

Quality criteria have to be completed with other instruments (indicators, reference parameters, etc.) in order to be operationalised.

The quality framework developed in this work was conceived for the German context, but can be used in other countries. Learners are integrated in the concept as a determinant of quality.

The purpose of this paper is to present an IDEF₀ framework model for the post-occupancy evaluation of school facilities, and the findings of a case study to demonstrate the applicability of the framework.

The framework model consists of five sequential processes, namely: first, identify the performance requirements of school facilities; second, conduct a walk-through evaluation and a focussed group discussion; third, develop and administer a user satisfaction survey; fourth, analyze the collected data and report the findings; and fifth, develop a plan of remedial actions.

The case study demonstrates the applicability of the framework through presenting the findings of an indicative evaluation of the major technical and functional elements of performance carried out on a school building in city of Khobar, Eastern Province of Saudi Arabia. The school users were satisfied with the qualities of the thermal comfort, visual comfort, fire protection, functional spaces in the school and the interior and exterior appearance of the school. The case study also resulted in developing a plan of remedial actions to improve the performance of the school.

The framework model provides a descriptive and systematic approach for evaluating the technical and functional performance of existing school facilities. The approach followed in collecting the data, designing the user satisfaction survey, analyzing and reporting the findings can be applied to any school building, upon the needed customization, irrespective of location.

The paper is particularly beneficial for design professionals, school administrators and facilities managers responsible for the design and operation of school facilities.

Why evaluate quality in Library and Information Science (LIS) schools? From a historical perspective, quality assurance always has been considered a strategic issue by LIS schools for improvement of the teaching and learning experience and for accountability. Internationalization has added a new role to quality assurance in LIS. In terms of the context of the World Trade Organization General Agreement on Trade in Services (WTO-GATS), LIS is increasingly recognized as part of the knowledge sector. The WTO-GATS has approved a multilateral framework that sets out rules for the conduct of international trade in services, including educational services. The GATS includes both general rules—for example, those related to the transparency of trade-related regulations—and a framework for specific commitments under which countries choose whether, and under what conditions, to allow access to their markets for foreign suppliers. The provisions in the GATS related to trade regulations and ways countries choose to allow access to their markets are relevant to the recognition of international standards or qualifications for professionals. Although not mandatory, international standards are encouraged, both for quality assurance of LIS school offerings in general, and for recognition of a specific LIS school outside its home country. Additionally, in the context of an increasingly internationalized job market, employers need reliable information on how to evaluate specific higher education degrees and assess degrees recognized and granted in their domestic market. The goals are to facilitate the mobility of students and to increase employability. The need to reinforce the comparability of higher education internationally through quality assurance systems is now becoming more pressing.

To develop a framework for evaluating the quality of Portuguese health care organisations based on the relationship between customers and providers, to define key variables related to the quality of health care services based on a review of the available literature, and to establish a conceptual framework in order to test the framework and variables empirically.

Systematic review of the literature.

Health care services quality should not be evaluated exclusively by customers. Given the complexity, ambiguity and heterogeneity of health care services, the authors develop a framework for health care evaluation based on the relationship between customers (patients, their relatives and citizens) and providers (managers, doctors, other technical staff and non‐technical staff), and considering four quality items (customer service orientation, financial performance, logistical functionality and level of staff competence).

This article identifies important changes in the Portuguese health care industry, such as the ownership of health care providers. At the same time, customers are changing their attitudes towards health care, becoming much more concerned and demanding of health services. These changes are forcing Portuguese private and public health care organisations to develop more marketing‐oriented services. This article recognises the importance of quality evaluation of health care services as a means of increasing customer satisfaction and organisational efficiency, and develops a framework for health care evaluation based on the relationship between customers and providers.

Purpose – Health system performance depends on production and use of quality health data and information. Routine health information systems (RHIS) are defined as systems that provide information at regular intervals of a year or less to meet predictable information needs. These include paper-based or electronic health records and facility- and district-level management information systems. RHIS are receiving increasing attention as an essential component of efficient, country-owned, integrated national systems. To guide investment decisions on RHIS, evidence is needed on which types of RHIS interventions work and which do not.

Design/methodology/approach – This chapter is a systematic review of the literature on the evaluation of RHIS interventions in low- and middle-income countries, starting from the premise that investments in RHIS could be better understood and so produce greater benefits than they currently do.

Findings – We describe the conceptual literature on the determinants of RHIS performance and its role in improving health systems functioning, discuss the evidence base on the effectiveness of strategies to improve RHIS performance, provide an overview of RHIS evaluation challenges, and make suggestions to improve the evidence base.

Originality/value – The goal is to help ensure that (a) RHIS interventions are appropriately designed and implemented to improve health systems functioning and (b) resulting RHIS information is used more effectively.

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

With the increasing popularity of online courses, their quality has become a public concern. Based on the perspective of knowledge management, this study aims to identify comprehensive and granular quality factors of online courses and analyze the relationships between the factors.

Following the principles of the grounded theory, interpretive structural modeling and cross-impact matrix multiplication applied to classification (MICMAC) analysis methods, this research uses reviews and comments garnered from Zhihu, which is the most popular online question-and-answer community in China, to conduct the analysis.

Based on the text data, 50 factors that potentially affect the quality of online courses are obtained. The analysis identifies the hierarchical relationships and dependent correlations between the factors.

The research uses the knowledge transformation model to classify content elements according to their degree of descriptiveness and provides practical and effective suggestions for improving the quality of online courses.

This paper aims to demonstrate the approach taken in delivering the quality and impact elements of Knowledge for Healthcare, the strategic development framework for National Health Service (NHS) library and knowledge services in England. It examines the work undertaken to enhance quality and demonstrate the value and impact of health library and knowledge services. It describes the interventions developed and implemented over a five-year period 2015–2020 and the move towards an outcome rather than process approach to impact and quality.

The case study illustrates a range of interventions that have been developed, including the outcomes of implementation to date. The methodology behind each intervention is informed by the evidence base and includes professional engagement.

The outcomes approach to the development and implementation of quality and impact interventions and assets provides evidence to demonstrate the value of library and knowledge staff to the NHS in England to both high-level decision-makers and service users.

The interventions are original concepts developed within the NHS to demonstrate system-wide impacts and change. The Evaluation Framework has been developed based on the impact planning and assessment (IPA) methodology. The interventions can be applied to other healthcare systems, and the generic learning is transferable to other library and knowledge sectors, such as higher education.