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Many healthcare institutions, such as hospitals, have recently implemented quality improvement initiatives such as Lean Six Sigma (LSS). However, only a few have sustained the initiatives and remained successful. One of the main reasons for the failure of LSS implementation is that managers tend to view LSS as individual projects. Managers lack a Change Management (CM) focus during the implementation. The primary purpose of this study is to document the implementation of LSS through a CM approach to improve sustainability.

Define-Measure-Analyse-Improve-Control (DMAIC) and the Awareness-Desire-Knowledge-Ability-Reinforcement (ADKAR), a popular CM approach, are combined to propose a new framework. The usefulness of the proposed framework is demonstrated using a case study in a multispeciality hospital located in southern India.

The study found that several factors are responsible for the high Length of Stay (LOS) for patients in the Emergency Department (ED). By implementing this proposed model to implement LSS and taking corrective actions, the average LOS was reduced from 267 to 158 min (a 40% reduction approximately).

The complete step-by-step approach is explained, and the LOS was considerably reduced during the pilot project. The findings will provide valuable insights for healthcare practitioners to understand the steps involved in the combined DMAIC-ADKAR model. The findings would also give healthcare practitioners the confidence to identify suitable tools and implement LSS in organisations where the practitioners work.

According to the authors' knowledge, this is the first study that synergises two models (DMAIC and ADKAR) into a single framework to implement in a hospital.

The goal of this article is to provide an overview of healthcare entrepreneurship, both in terms of its current trends and future directions.

The article engages in a systematic review of extant research on healthcare entrepreneurship using the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) as the review protocol and bibliometrics or scientometrics analysis as the review method.

Healthcare entrepreneurship research has fared reasonably well in terms of publication productivity and impact, with diverse contributions coming from authors, institutions and countries, as well as a range of monetary and non-monetary support from funders and journals. The (eight) major themes of healthcare entrepreneurship research revolve around innovation and leadership, disruption and technology, entrepreneurship models, education and empowerment, systems and services, orientations and opportunities, choices and freedom and policy and impact.

The article establishes healthcare entrepreneurship as a promising field of academic research and professional practice that leverages the power of entrepreneurship to advance the state of healthcare.

The article offers a seminal state of the art of healthcare entrepreneurship research.

This study demonstrates how becoming a high-reliability institution in health care is a priority, given the high-risk environment in which an error can result in harm. Literature conceptually supports the need for highly reliable health care facilities but does not show a comprehensive approach to operationalizing the concept into the daily workforce to support patients. The Veterans Health Administration closes the gap by documenting a case study that not only demonstrates specific actions and functions that create a high-reliability organization (HRO) for safety and improvement but also created a learning organization by spreading the knowledge to other facilities.

The authors instituted a methodology consisting of assessments, training and educational simulations to measure, establish and operationalize activities that identified and prevented harmful events. Visual communication boards were created to facilitate team huddles and discuss improvement ideas. Improvements were then measured and analyzed for purposeful outcomes and return on investment (ROI).

HRO can be operationalized successfully in health care systems. Measurable outcomes verified that psychological safety was achieved through the identification and participation of 3,184 process improvement projects over a five-year period, which yielded a US$2.8m ROI. Documented processes and activities were used for educational teachings, which were disseminated to other Veteran Affairs Medical Center’s through the Truman HRO Academy.

This case study is limited to one hospital in the Veterans Health Administration (VHA) network. As the VHA continues to deploy the methods outlined to other hospitals, the authors will perform incremental data collection and ongoing analysis for further validation of the HRO methods and operations. Hospitalists can adapt the methods in the case study for practical application in a health care setting outside of VHA. Although the model is rooted in health care, the methods may be adapted for use in other industries.

This case study overcomes the limitations within literature regarding operationalizing HRO by providing actual activities and demonstrations that can be implemented by other health care facilities.

In this paper, the seismic behavior of the gusset plate moment connection (GPMC) exposed to the post-earthquake fire (PEF) is investigated.

For this purpose, for the sake of verification, first, a numerical model is built using ABAQUS software and then exposed to earthquakes and high temperatures. Afterward, the effects of a series of parameters, such as gusset plate thickness, gap width, steel grade, vertical load value and presence of the stiffeners, are evaluated on the behavior of the connection in the PEF conditions.

Based on the results obtained from the parametric study, all parameters effectively played a role against the seismic loads, although, when exposed to fire, it was found that the vertical load value and presence of the stiffener revealed a great contribution and the other parameters could not significantly affect the connection performance. Finally, to develop the modeling and further study the performance of the connection, the 4 and 8-story frames are subjected to 11 accelerograms and 3 different fire scenarios. The findings demonstrate that high temperatures impose rotations on the structure, such that the story drifts were changed compared to the post-earthquake drift values.

The obtained results can be used by engineers to design the GPMC for the combined action of earthquake and fire.

The purpose of this paper is to demonstrate the close relationship between the disciplines of law and health-care studies. This interrelation has become particularly evident during the spread of the COVID-19 pandemic, when restrictive human rights provisions have been initiated by many states for the sake of public health. Research focuses on the notional proximity of the principle of proportionality and its health-care correlative: effectiveness. It also goes through the influence of acceptance rates for the application of restrictive measures.

Research focuses on interdisciplinary literature review, taking into consideration judicial decisions and data on acceptance rates of restrictive human rights measures in particular. Analysis goes in depth when two categories of restrictive human rights measures against the spread of the pandemic are examined in depth: restrictive measures to achieve social distancing and mandatory vaccination of professional groups.

Restrictive human rights measures for reasons of public health are strongly affected by the need for effective health-care systems. This argument is verified by judicial decision-making which relies to the necessity of health-care effectiveness to a great extent. The COVID-19 pandemic offers a laminate example of the two disciplines’ interrelation and how they infiltrate each other.

Further implications for research point at the need to institutionalize a cooperative scheme between legal and health-care decision-making, given that this interrelation is strong.

The originality of this paper lies on the interdisciplinary approach between law and health-care studies. It explains how state policies during the pandemic were shaped based on the concepts of effectiveness and proportionality.

The purpose of this paper is to expand and analyze deeply customer emotions, concretize the levels of positive or negative emotions with the aim of using machine learning methods, and build a model to identify customer emotions.

The study proposed a customer emotion detection model and data mining method based on the collected dataset, including 80,593 online reviews on agoda.com and booking.com from 2009 to 2022.

By discerning specific emotions expressed in customers' comments, emotion detection, which refers to the process of identifying users' emotional states, assumes a crucial role in evaluating the brand value of a product. The research capitalizes on the vast and diverse data sources available on hotel booking websites, which, despite their richness, remain largely unexplored and unanalyzed. The outcomes of the model, pertaining to the detection and classification of customer emotions based on ratings and reviews into four distinct emotional states, offer a means to address the challenge of determining customer satisfaction regarding their actual service experiences. These findings hold substantial value for businesses operating in this domain, as the findings facilitate the evaluation and formulation of improvement strategies within their business models. The experimental study reveals that the proposed model attains an exact match ratio, precision, and recall rates of up to 81%, 90% and 90%, respectively.

The study has yet to mine real-time data. Prediction results may be influenced because the amount of data collected from the web is insufficient and preprocessing is not completely suppressed. Furthermore, the model in the study was not tested using all algorithms and multi-label classifiers. Future research should build databases to mine data in real-time and collect more data and enhance the current model.

The study's results suggest that the emotion detection models can be applied to the real world to quickly analyze customer feedback. The proposed models enable the identification of customers' emotions, the discovery of customer demand, the enhancement of service, and the general customer experience. The established models can be used by many service sectors to learn more about customer satisfaction with the offered goods and services from customer reviews.

The research paper helps businesses in the hospitality area analyze customer emotions in each specific aspect to ensure customer satisfaction. In addition, managers can come up with appropriate strategies to bring better products and services to society and people. Subsequently, fostering the growth of the hotel tourism sector within the nation, thereby facilitating sustainable economic development on a national scale.

This study developed a customer emotions detection model for detecting and classifying customer ratings and reviews as 4 specific emotions: happy, angry, depressed and hopeful based on online booking hotel websites agoda.com and booking.com that contains 80,593 reviews in Vietnamese. The research results help businesses check and evaluate the quality of their services, thereby offering appropriate improvement strategies to increase customers' satisfaction and demand more effectively.

Globally, prefabrication in housebuilding has evolved as an innovative approach to attain sustainability and affordability. However, the SC, including non-producers and producers, of prefabricated housebuilding projects is still not perceptually aligned, hindering innovation diffusion. This paper investigates the contemporary industry perspective on PHB for conceptualisation, market share and growth, innovation diffusion and the producer's role in the context of New Zealand.

An exploratory qualitative research design was chosen to learn the perceptual stance of the industry. A semi-structured survey was conducted, followed by interviews with selected supply chain participants, who were producers and non-producers and had relevant experience in the PHB industry.

This study reports the common terminologies used by supply chain members, with justification and explanation. Further, the perceived market share and growth of the PHB industry are obtained and compared with subsequent studies to determine the capability and capacity. The perception of the diffusion of PHB by type is reported to portray the overall trend of the industry. In the last, the role of producers as the suppliers of PHB projects is investigated to establish the stakeholder positional criticality.

This study can help researchers and practitioners gain insight into the PHB industry from a multi-dimensional perspective. This study is a potential first step to formalise the policy, programme, strategies and action plan for the uptake of the PHB in the New Zealand.

PHB diffusion in the supply chain perspective, considering multi-dimensional aspects, has not been considered in previous studies as government agencies produce most of the literature. This academic research establishes the theoretical linkage towards PHB diffusion and reports the current status.

This study aims to analyze the determinants influencing Chinese manufacturing companies in implementing lean manufacturing (LM).

The determinants to be explored in this study consist of technological, organizational and environmental (TOE) dimensions. A questionnaire survey was conducted on Chinese manufacturing companies, and 208 samples were analyzed.

The findings show that the relative advantage of LM and organizational support have significantly positive effects on Chinese manufacturing firms’ adoption of LM. The complexity of LM, quality of human resources, organizational readiness, customer pressure, international situation, governmental support and environmental uncertainty do not have significant effects.

This paper contributes to the literature by using the TOE model to explore the factors influencing LM adoption in the Chinese manufacturing industry.

Contemporary entrepreneurial ecosystem models and frameworks advocate that culture is a criterion for entrepreneurial intention and central to entrepreneurship discourse. However, there is limited research from resource-constrained economies, such as sub-Saharan Africa and at a sub-national level. Responding to calls for bottom-up perspectives hinged on local context and heterogeneous nature, this paper aims to provide an in-depth understanding from multiple perspectives about the effect that culture and entrepreneurial intention have on the entrepreneurship process and performance in Nelson Mandela Bay, South Africa.

A mixed-method research design followed a sequential independent process consisting of two phases. Phase 1 included the dissemination of questionnaires to economically active participants, and 300 responses were statistically analysed. In Phase 2, 15 semi-structured interviews with influential economic development agents were conducted.

The results indicated that social legitimacy towards entrepreneurship existed and self-employment was viewed positively. However, self-employment endeavours were mainly necessity driven, and the systemic low levels of innovation, poor business competitiveness and the inability to scale were highlighted. The findings indicated that individuals venturing into business had a culture of being dependant on the government, lacking a risk appetite, fearing failure, with disparate groups suffering from a poor legacy of entrepreneurship.

Despite research done on the role of culture and entrepreneurial intention on entrepreneurial ecosystems, there are few case studies showing their influence at a sub-national level. This study responds to calls for studies on a sub-national level by exploring the influence that culture and entrepreneurial intention have on entrepreneurship in a resource-constrained metropole.

This study develops a robust model to measure intellectual capital efficiency (ICE). It also analyzes ICE across Gulf companies, sectors and countries.

This study uses data envelopment analysis (DEA), the Malmquist productivity index (MPI), difference tests and additional analyses on a dataset consisting of 276 firm-year observations.

The findings indicate that the study model is robust to additional analysis. The results show significant differences in ICE between firms during the study period and noteworthy differences between countries, where the Qatari and Bahraini firms achieved the best ICE compared to other countries.

The results of this study have significant ramifications for increasing knowledge of ICE analysis models among relevant parties. In addition, the findings may affect trading strategies because investors and financiers are motivated by the potential for lucrative financial returns on their investments in companies that prioritize ICE strategies.

This research contributes to the literature by proposing a robust model for estimating the ICE. It also compares ICE across Gulf companies, industries and countries to shed light on their ICE challenges.