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Researchers have widely explored and associated corporate social responsibility with firm success. Measuring the relationship between corporate social responsibility (CSR), service quality, corporate reputation, and brand preference by drawing on the stakeholder theory in healthcare industry and developing countries remains a substantial research gap.

Based on quantitative research and convenience sampling, data for the study were collected from 320 patients who have undergone treatments in 5 different private hospitals in Tehran, Iran. We analyzed the data using the Smart PLS 3.0 structural equation modeling technique.

The survey revealed that service quality and CSR are positively linked with corporate reputation, leading to brand preference in the healthcare sector. In addition, the mediating role of brand reputation in the relationship between corporate social responsibility, service quality and brand preference were confirmed.

The survey was performed in the context of the healthcare industry; however, additional studies are necessary to extrapolate the results to other fields, such as education and food. This research helps guide policymakers, administrators, healthcare managers, and researchers by highlighting the contribution and role of service quality, corporate social responsibility, and corporate reputation in achieving a hospital’s performance.

To the best of the authors’ knowledge, this study also extends research in the diverse literature by examining the relationship between CSR, service quality, corporate reputation, and brand preference by illustrating the stakeholder theory in the context of the healthcare sector.

Technology-enabled healthcare focuses on providing better information flow and coordination in healthcare operations. Technology-enabled health services enable hospitals to manage their resources effectively, maintain continuous patient engagement and provide seamless services without compromising their perceived quality.

This study investigates the role of technology-enabled health services in improving perceived healthcare quality among patients. Data are collected from the users (n = 418) of health platforms offered in multi-specialty hospitals. Multiple learners are employed to accurately represent the users' perceived quality regarding the perceived usefulness of the features provided via these digital health platforms.

The best-fitted model using a decision tree classifier (accuracy = 0.86) derives the accurate significance of features offered in the digital health platform in fostering perceived healthcare quality. Diet and lifestyle recommendations (30%) and chatting with health professionals (11%) are the top features offered in digital health platforms that primarily influence the perceived quality of healthcare among users.

The predictability of perceived quality with the individual features existing in the digital health platform, the significance of the features on the perceived healthcare quality and the prediction rules showing the combined effect of features on healthcare quality can help healthcare managers accelerate digital transformation in hospitals by improving their digital health platform, designing and offering new health packages while strengthening their e-infrastructure.

The study represents perceived healthcare quality with the features offered in digital health platforms using machine learners based on users' post-pandemic experience. By advancing digital platforms with more patient-centric features using emerging technologies, this model can further foresee its impact on the perceived quality of healthcare, offering valuable directions to healthcare service providers. The study is limited to focusing on digital health platforms that can deal with people's general healthcare needs.

The primary objective of this study is to conduct a comprehensive literature review focused on the concept of service quality within the healthcare sector. This research aims to categorize and analyze the various dimensions associated with service quality.

The systematic literature review methodology was employed to accomplish current study goals, and specific criteria were utilized to select relevant research articles spanning the years from 2000 to 2023. Ultimately, 57 articles met the criteria and were included in the study.

Through a meticulous review of selected articles, our research identified and categorized 29 distinct measures for evaluating service quality in the healthcare sector. These measures were further grouped into five overarching categories, namely: overall service quality, personal characteristics, healthcare facility administration, patient attributes and the servicescape. Our investigation highlighted that the dimensions commonly utilized to assess service quality in healthcare primarily draw from the SERVQUAL framework. Additionally, there is significant emphasis on measurements related to the physical environment's quality, overall patient satisfaction and behavioral intention.

This review offers original value by synthesizing diverse literature on healthcare service quality, highlighting SEVQUAL dimensions and critical variables used for assessment. It provides insight into the subjective nature of service quality and varied sampling methods and contributes to enhancing service quality and patient satisfaction in healthcare settings.

This study aims to investigate the role of information normalization in online healthcare consultation, a typical complex human-to-human communication requiring both effectiveness and efficiency. The globalization and digitization trend calls for high-quality information, and normalization is considered an effective method for improving information quality. Meanwhile, some researchers argued that excessive normalization (standardized answers) may be perceived as impersonal, repetitive, and cold. Thus, it is not appreciated for human-to-human communication, for instance, when patients are anxious about their health condition (e.g. with high-risk disease) in online healthcare consultation. Therefore, the role of information normalization in human communication is worthy to be explored.

Data were collected from one of the largest online healthcare consultation platforms (Dxy.com). This study expanded the existing information quality model by introducing information normalization as a new dimension. Information normalization was assessed using medical templates, extracted through natural language processing methods such as Bidirectional Encoder Representations from Transformers (BERT) and Latent Dirichlet Allocation (LDA). Patient decision-making behaviors, namely, consultant selection and satisfaction, were chosen to evaluate communication performance.

The results confirmed the positive impact of information normalization on communication performance. Additionally, a negative moderating effect of disease risk on the relationship between information normalization and patient decision-making was identified. Furthermore, the study demonstrated that information normalization can be enhanced through experiential learning.

These findings highlighted the significance of information normalization in online healthcare communication and extended the existing information quality model. It also facilitated patient decision-making on online healthcare platforms by providing a comprehensive information quality measurement. In addition, the moderating effects indicated the contradiction between informational support and emotional support, enriching the social support theory.

Healthcare has undergone multiple phases in gaining understanding, accepting and implementing quality and safety, with the last 3 decades being crucial and decisive in making progress. During that time, safety has always been quoted along with quality, but the cost of error in healthcare (both in human lives and monetary cost) has been continuing to rise.

This article discusses the authors’ expert perspective in comparison to the industry’s research and practice outputs.

Healthcare has not yet defined quality and safety. This is allowing the misconception that already established quality management systems (QMSs) are fit for safety purposes as well. Even though aviation has acted as a paradigm for healthcare, further alignment in embedding safety management systems (SMS) has yet to be realised.

In this paper, the distinct nature of safety and its detachment of quality is being discussed, along with the need for clear and safety specific processes. Setting common language is the first step in establishing appropriate safety processes within SMSs, operating in tandem with QMSs, to promote patient safety successfully.

The healthcare sector relies on knowledge management systems to improve knowledge flows and effectively capture, leverage and share knowledge with several organizational stakeholders. However, knowledge as a resource represents a social construct that involves additional managerial complexities and challenges, including undesirable knowledge behaviours. The aim of the current study is to provide insight on how knowledge management systems, knowledge hoarding, knowledge hiding and task conflict shape the quality of care provided by hospitals. We propose and test an original revealing model.

We follow a quantitative approach to address the structural relationship between variables using a combination of factor analysis and multiple regression analysis. The model is tested adopting a structural equation modelling approach and using survey data conducted to 318 healthcare professionals working in Portuguese hospitals.

The main findings suggest that knowledge hiding is positively related to task conflict in hospitals, and task conflict negatively influences quality of care. Knowledge management systems directly and indirectly (via knowledge hoarding) promote quality of care. Moreover, knowledge management systems also mitigate the negative influence of task conflict over quality of care. We propose a final corollary on the relevant role of HRM as the backstage for the model.

Our research offers a novel insight into an overlap of organizational behaviour and healthcare management research. It provides an original framework on knowledge management systems, counterproductive knowledge behaviours and task conflict in hospital settings.

Our research offers a novel insight into an overlap of organizational behaviour and healthcare management research. It provides an original framework on knowledge management systems, counterproductive knowledge behaviours and task conflict in hospital settings.

Healthcare organizations have been facing challenges due to high costs and low efficiency in health services. The growth of costs and losses caused by avoidable mistakes lead to the search for solutions, and Health Lean Management appears as a potential solution to help in solving service quality problems, as well as reducing risks. This study aims to analyse the state of the art in the literature centred on the Lean approach in the context of risk management in healthcare organizations, and to identify new research opportunities, highlighting possible lines of future research.

Following a systematic literature review approach, 51 papers were considered relevant for this research, and reviewed to explore the development of literature in this area.

Based on the results, five main research streams were identified: (1) risk management oriented towards patient safety; (2) risk management oriented towards employee safety; (3) importance of attitudes and behaviours in risk reduction projects; (4) Lean tools used in healthcare risk management and (5) Integration of approaches. Moreover, several shortcomings were identified in literature.

Identified shortcomings represent significant opportunities for further research development.

Efficiency and quality are primary factors for the survival of health systems. The evaluation of the efficiency of the healthcare system is a crucial component of promoting long-term health policy actions. Healthcare capacity indicators provide a basis for evaluating and comparing the performance of different healthcare organizations. Intrinsic quality indicators are Donabedian (1980)’s structural and process elements of quality of healthcare. This study aims to integrate capacity and intrinsic quality indicators of healthcare while measuring the efficiency of provinces by using radial and non-radial efficiency measurement techniques.

Efficiency analysis performed in Turkey from 2015 to 2020 by performing input-oriented radial, nonradial, and super-efficiency estimates for 81 provinces of Turkey by incorporating capacity and intrinsic quality indicators into the different model specifications.

Radial and nonradial efficiency results have an increasing trend over the study years obtained from the efficiency models showing high average scores obtained from the models that include intrinsic quality of care indicators. Statistically significant mean rank differences are observed between different radial efficiency models for all study years (p < 0.001). Negative and moderate level correlations were observed between radial efficiency results and quality of care indicators (r < 0.70).

Under long-term centralized health policies, increases in efficiency result in decreased intrinsic quality of care indicators. A better synthesis of health system capacity and intrinsic healthcare quality indicators is necessary to generate evidence-based health systems.

This study aims to fully assess the readiness for Lean Six Sigma (LSS) and Quality Performance Improvement (QPI) in an Italian Public Healthcare ecosystem.

Drawing from previously established survey development and adaptation protocols, a replication study was carried out; Lean, Six Sigma and QPI were extracted and validated through confirmatory factor analysis in an Italian Public Healthcare setting, with a sample of health professionals from the Campania region.

This study reports the adaptation of an existing scale for measuring LSS and QPI in an Italian public healthcare organisation. This analysis extracts six conceptual domains and constitutes an original adaptation of an existing scale to assess the readiness to adopt Lean, Six Sigma and Quality Performance in Italian Public Health Organizations. The constructs show strong levels of internal consistency, as demonstrated by each item factor loading and each subscale reliability.

Managers, policymakers and academics can employ the proposed tool to assess the public healthcare ecosystem’s capability to implement LSS initiatives and strategies to improve quality performance.

This is one of the first studies to assess cross-regional organisational readiness for LSS and QPI in an Italian Public Healthcare environment at this scope and level.

Quality improvement has developed and spread, and today, all Swedish Regions emphasize that their strategies are based on systematic improvement. This paper aims to describe and illuminate the development of Quality Improvement (QI) in Swedish healthcare and welfare organizations by using publications in a Swedish context.

The overview synthesis is inspired by a scoping literature review approach of relevant literature. All publications relevant to Swedish healthcare and welfare settings between 1992 until 2020 were included.

In all, 213 papers, 29 books and chapters and 34 dissertations related to QI and research in Swedish healthcare and welfare context were identified. From 2011 to 2020, the publication rate increased rapidly. Six different focus areas emerged: systematic and value-creating improvement work; collaboration between organizations and healthcare providers; use of improvement methods and (theoretical) models; leadership and learning; measurements, quality registers and follow-up; and involvement and patient safety. Further QI development in Swedish healthcare and welfare points to an increased importance of collaboration between organizations and coproduction with beneficiaries for the healthcare and welfare services.

This paper is one of the first to describe and illuminate the QI development in the healthcare and welfare sector in a country. The trajectory also points to a need for coproduction to handle future challenges.