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This study aims to present Lean Six Sigma (LSS) deployment and sustainment strategies for the healthcare sector from a multi-level perspective. The objective is to present LSS implementation insights to enable policymakers, practitioners and academicians to test and develop an LSS framework for healthcare sectors.

The strategies identified are the result of a multi-method research design involving literature review, action research (AR) and Delphi study. Further, the AR portion of the study involved more than 10 years of projects focused on the deployment of LSS in the healthcare sector.

The strategies include a holistic view from the multi-level perspective, considering the Top Management Level, Middle Management Level and Operational Level. The authors ascertained 27 strategies across the three levels of organizational structure for the effective deployment of LSS. Further, the authors present a customized LSS “pocket guide” from the healthcare perspective for quick reference.

The strategies delineated in this study are based on the Indian healthcare section only; thus, further research in additional geographic contexts is needed. Also, further research is necessary to provide additional empirical validation of the effects of the identified strategies on LSS program outcomes and to verify that the strategies operate at the proposed organizational levels. Future research should also focus on identifying the interrelationships between strategies within and across levels, developing a “road map” for LSS implementation in hospitals and designing the LSS curriculum for medical schools and other medical training programs.

Observations of this study can contribute to developing a holistic framework for successful LSS implementation in the healthcare sector for academicians, practitioners and policymakers. This, in turn, ensures an enhanced value proposition, improved quality of life and reduced healthcare operational costs. Thus, it ensures a win-win situation among all the stakeholders of the healthcare sector.

The strategies put forth will enable the LSS researchers, academicians and, more particularly, practitioners to delve deeper into specific enablers and safeguard the LSS deployment from backlash. The research has two significant benefits. Firstly, it enhances the understanding of LSS from the healthcare perspective. Secondly, it provides direction for future studies with specific components for hospitals’ LSS framework, which can be further tested, refined and improved.

This study aims to develop and implement an initial framework for assessing progress in lean implementation within an higher education institution (HEI). It includes developing preliminary findings regarding the impacts of lean implementation in the HEI case organization and comparing outcomes from this assessment to outcomes from other published sources.

Existing literature on lean, particularly in an HEI context, was used to develop a preliminary lean assessment framework for HEIs. Quality and continuous improvement literature were also compared to the proposed assessment framework to further validate the approach. This assessment framework was then utilized to evaluate lean implementation at a large public university (LPU) in the U.S.

The paper presents the framework as well as the major findings from the Large Public University (LPU)’s assessment. The assessment findings are further compared to other HEI quality measures and lean assessments done in other industries. Overall, the findings suggest that the assessment framework provides valuable insight to HEI organizations implementing lean.

The research intends to support lean assessment standardization efforts by proposing a preliminary lean assessment framework for the HEI, grounded in research trends, research findings, identified gaps in the research, and case study outcomes. To the research team's knowledge, this is the first lean assessment framework proposed for HEIs and also contributes to research gaps related to service industry frameworks and those containing both practices and outcomes. The framework can be used by other researchers as a foundation for additional conceptual and empirical developments on the topic and by researchers and practitioners seeking to understand and assess lean implementation progress in the HEI.

A systematic literature review (SLR) was used to identify and analyze literature related to use of system dynamics (SD) applications in organizational performance measurement (PM) research. The purpose of this article is to present the results of a thematic analysis (TA) conducted to synthesize existing empirical evidence, investigate trends and evaluate developments in the research area.

A SLR was conducted resulting in a dataset of 97 articles in this research area. Using TA, major themes/subthemes were inductively synthesized to explore the current development and emerging trends and provide guidance for future research.

The TA resulted in seven themes in the research area – Enhancing knowledge, Approaches to operationalizing PM systems, Utilizing simulation models, Improving organizational outcomes, Achieving strategic alignment, Applying systems thinking and Identifying critical variables. The analysis suggests that although SD has the potential to improve PM systems, there are many limitations and challenges that must be addressed to improve implementation and practical applications. In addition, the results showed that much of the work is exploratory and many fail to fully validate their models suggesting that this research is still in an relatively early phase of development.

The results of this study are limited to the 97 articles identified using the SLR protocol. Although the search was designed to be comprehensive, there may be other relevant literature that was excluded. Further, the TA was limited to addressing the research questions.

A key insight for managers is that these tools would support decision-makers in understanding performance behaviors and identifying performance drivers for improvement. This suggests that stakeholders can adopt the approach to improve understanding and effectiveness of PM, and to enhance strategic decision-making.

This study provides a distinct and thorough analysis of this research area by conducting an inductive synthesis of developments and challenges and guidance for future research and practice. The resulting thematic model, identified code definitions and proposed framework of strategies to overcome challenges, provide a general overview and resource to support future studies in the research area and facilitate practical use of SD capabilities to support PM.

This case study aims to explore the appropriateness of an adaptive riding program for persons living with dementia through examining family members’ (care partners) reported outcomes.

Using convenience sampling, persons living with dementia and their care partners were recruited in Northern Colorado; after meeting inclusion criteria, they were invited to participate in the adaptive riding program. The program occurred for weekly, hour-long sessions for eight weeks. Field notes were collected during each session, and semi-structured interviews were conducted with five care partners after the program and analyzed by using theoretical thematic analysis.

Care partners found the adaptive riding program appropriate. Reported outcomes comprised three themes: well-being, meaning through social connections and function in daily life and aligned with the positive emotions, engagement, relationships, meaning, accomplishment (PERMA) theory of well-being.

To the best of the authors’ knowledge, this is the first study to explore the appropriateness of an adaptive riding program for persons living with dementia and their care partners who broadened understandings of the emotional, social and physical benefits. Findings support the inclusion of care partners in adaptive riding and may inform health-care providers’ recommendations for such programs.

Lean is a continuous improvement methodology that has succeeded in eliminating waste in a variety of industries. Yet, there is a need for more research on Lean implementation in several under-studied contexts, including crisis situations such as those created by the recent COVID-19 pandemic. This research investigates how Lean programs were impacted by COVID-19, while previous research has primarily explored how Lean was used to solve problems created by the pandemic.

A mixed-method research approach was used to analyze employee feedback on how COVID-19 impacted the Lean programs using data from various levels of four energy-based utilities in the United States. First, an online questionnaire collected qualitative and quantitative data from a broad sample of participants. Then, a follow-up semi-structured interview allowed the elaboration of perceptions related to the research question using a smaller sample of participants.

Out of the 194 responses from the four companies, only 41% of the respondents at least somewhat agreed that COVID-19 impacted the Lean program at their company; of the remaining 59%, 35% indicated they were neutral, while 24% disagreed. The themes from the qualitative portion indicated that, while employees believed their companies had successfully found a new way to do Lean within the constraints of not always being in person, the collaboration and engagement were more challenging to sustain, and COVID-19 also otherwise made it more difficult to implement Lean. Meanwhile, some believed there was no impact on the Lean program.

The COVID-19 and Lean peer-reviewed literature published from 2020 to September 2023 focused primarily on using Lean to address problems created by the COVID-19 pandemic vs studying the pandemic's impact on Lean programs. This research partially fills this literature gap in understanding the impact COVID-19 had on Lean initiatives.

Green lean six sigma (GLSS) is a sustainable development approach that leads to improved patient care with improved safety and quality of service to patients. This study aims to identify, study, model and analyze GLSS success factors for the Indian health-care facility.

Interpretive structural modeling (ISM) and Impact Matrix Cross-Reference Multiplication Applied to a Classification analyses have been used to understand the hierarchical structure among the GLSS success factors. This enabled the development of dependency relationships between success factors, in particular, which factors support the development of other factors.

Specifically, this study found that the success factors “commitment of management” and “financial availability” are the most critical to GLSS implementation success, as they support the development of all other success factors. Meanwhile “embedding sustainable measures at each stage of the service”; “the capability and effectiveness of real-time data collection”; and “feedback and corrective actions” most directly support the GLSS implementation in the health-care facility and serve as the final indicators of implementation progress.

The major implication of this research work lies in suggesting a direction for practitioners to execute the GLSS approach through a systematic understanding of classification and structural relationships among different enablers. This study also facilitates health-care managers to explore different GL wastes in hospitals and challenges to sustainability pursuits in health-care that assist in an organization’s efforts toward sustainable development.

This research work is the first of its kind that deals with the identification and analysis of the prominent factors that foster the inclusive implementation of GLSS within the health-care facility.

The purpose of this paper is to identify, through an exploratory meta-analysis, which process- and outcome-related antecedents have the strongest relationship to overall team performance. The secondary objective is to create an understanding of the extent to which relative research interest in each construct to date has aligned with its reported effects.

This study uses a random-effects meta-analysis on studies that have measured the relationship between at least one process or outcome factor and overall team performance. The number of studies, effect size and between-study variances are captured and analyzed for each process/outcome factor. Prior literature has explored relationships between various process/outcome factors and overall team performance. This study expands on previous literature by examining a comprehensive set of process/outcome factors and their relative impact on overall team performance.

A meta-analysis of 190 effect sizes extracted from 52 empirical studies over the past two decades (1999–2020) showed the specific process and outcome factors that most strongly contributed to overall team performance were efficiency, schedule and innovation. In addition, only a weak correlation was found between process and outcome factors’ relationships with overall team performance and how often they are studied in the research community.

This study contributes to the body of knowledge on team performance by examining prior research to identify the relevant impact of various process and outcome factors on overall team performance. In addition, this study also assesses the extent to which research interest in these factors has appeared to match their relative impact. Analyzing the relative impact of various process and outcome factors allows researchers and practitioners to better identify methods to create improvement in overall team performance. Based on the findings, prioritizing efficiency, schedule and innovation may promote overall team performance.

The coronavirus (COVID-19) pandemic has led to a surge in demand for health-care facilities, medicines, vaccines and other health-care items. The purpose of this study is to investigate different facets of integrated Green Lean Six Sigma and Industry 4.0 approach in the context of COVID-19 for better healthcare management. Integrating Green Lean Six Sigma (GLSS) and Industry 4.0 (I4.0) has the potential to meet the modern demand of health-care units and also leads to improving the quality of inpatient care with better safety, hygiene and real-time diagnoses. A systematic review has been conducted to determine the tools/techniques, challenges, application areas and potential benefits for the adoption of an integrated GLSS-I4.0 approach within health-care facilities from the perspective of COVID management. Further, a conceptual framework of integrated GLSS-I4.0 has been proposed for better COVID management.

To conduct the literature review, the authors used the preferred reporting items for systematic reviews and meta-analysis and covers relevant papers from the arrival of COVID-19. Based on the systematic understanding of the different facets of the integrated GLSS-I4.0 approach and through insights of experts (academicians and health-care personnel), a conceptual framework is proposed to combat COVID-19 for better detection, prevention and cure.

The systematic review presented here provides different avenues to comprehend the different facets of the integrated GLSS-I4.0 approach in different areas of COVID health-care management. In this study, the proposed framework reveals that the Internet of Things, big data and artificial intelligence are the major constituents of I4.0 technologies that lead to better COVID management. Moreover, integration of I4.0 with GLSS aids during different stages of the COVID management, right from diagnosis, manufacture of items and inpatient and outpatient care of the affected person.

This study provides a significant knowledge database to the practitioners by understanding different tools and techniques of an integrated approach for better COVID management. Moreover, the proposed framework aids to grab day-to-day information from the affected people and ensures reduced hospital stay with better space utilization and the creation of a healthy environment around the patient. This inclusive implementation of the proposed framework will enhance knowledge base in medical areas and provides different novel prospects to combat other medical urgencies.

To the best of the authors’ knowledge, this study is the first of its kind to review different facets of the integrated GLSS-I4.0 approach with a view of the COVID health-care perspective and provides a conceptual framework.

Organizations spend considerable time and money educating individuals on Six Sigma; however, existing literature does not examine Six Sigma adoption at the individual level or the factors that impact individual Six Sigma adoption. The purpose of this paper is to increase the understanding of individual adoption of Six Sigma tools and methodology.

This paper used a single-site field study in a manufacturing organization to empirically test and refine a theory of the factors impacting Six Sigma adoption at the individual level.

Reaction to training, project management and project infrastructure were found to be significant input factors for individual Six Sigma adoption with an R² of 0.482, which indicates that about 48 per cent of the variation in Six Sigma adoption is explained by the input factors. All of the identified input factors were found to have a positive relationship with individual Six Sigma adoption, as well as positive correlations with each other.

This paper was not a controlled experiment or a longitudinal study, so it is not possible from the results of this research to prove causal relationships, although the literature supports a causal relationship between the input factors and outcome.

The findings of this paper will be useful to practicing organizations which seek to improve individual Six Sigma adoptions, as well as inform future Six Sigma adoption research.

Six Sigma adoption at the organizational level has been well documented in the existing literature. The successful adoption of Six Sigma in an organization is dependent, at least in part, to adoption Six Sigma at the individual level. A review of the existing literature indicates that there has been no research into individual adoption of Six Sigma tools and methodology.

Evidence suggests that hospitals are having problems achieving continuous improvement project (CIP) goals or sustaining their results. Therefore, the purpose of this paper is to identify those critical success factors (CSFs) most strongly related to CIP success in hospitals (Lean-Kaizen project, Lean Six Sigma project, Six Sigma projects, and Quality Improvement projects).

A retrospective survey was applied to any CIP leaders/facilitators from hospitals that conducted at least one CIP during the last two years.

Three main findings were obtained from the 116 valid responses. First, the level of importance of 47 out of 53 CSFs to achieve CIPs success in hospitals was assessed as very important or higher (4 or higher on a six-point scale). Second, there are important differences between the CSFs to achieve CIP success in hospitals in this research and previous investigations. Third, the type of CIP affects the level of importance of 16 out of 53 CSFs to achieve CIP success in hospitals.

Practitioners involved with CIPs activities in hospitals could use the knowledge extracted from this investigation to improve the impact of their CIPs. Future research should continue in two lines: test if the 53 CSFs for CIPs measure a unique factor and identify the main relationships or paths between CSFs for CIPs and CIP outcomes.