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The purpose of this paper is to explore the moderating role of Lean Six Sigma (LSS) practices in explaining the relationship between quality management practices (QMPs) and quality performance.

Partial least square-based structural equation modeling (PLS-SEM) was used to empirically examine the moderating effect of LSS practices on QMPs and quality performance in Malaysian medical device manufacturing companies.

Findings revealed that both QMPs and LSS practices have a significant and positive effect on quality performance. Furthermore, LSS practices served as a substitute for moderating the positive relationship between QMPs and quality performance in such a way that the relationship becomes weaker as LSS practices increase.

LSS is acknowledged as the most well-known hybrid methodology; however, due to its relative newness, it has not been studied in great detail. Unlike previous studies, this paper argued that Lean and Six Sigma practices are distinct from its predecessor TQM practices; moreover, both Lean and Six Sigma practices do not need to substitute QM/TQM practices instead of complimenting the QMPs. In addition, this study adds to the growing body of QM literature by empirically examine the effect of LSS practices in moderating the relationship between QMPs and quality performance.

With the growing pressure to gain optimum level of quality and speed, Lean Six Sigma (LSS) practices have drawn considerable attention as a viable alternative for process improvement. However, previous studies revealed that there is very little systematic and rigorous research to validate the claims. In this regard, this paper aims to empirically examine the effect of LSS practices on quality performance in the medical device manufacturing industry.

For this study, partial least square–based structural equation modeling (PLS-SEM) was used to empirically examine the effect of LSS practices on quality performance in Malaysian medical device manufacturing industry.

The findings of this paper revealed that LSS practices have a significant and positive effect on quality performance in the medical device manufacturing industry.

This paper will serve as a valuable implication for industry practitioners in providing them with a clearer managerial direction to exploit the strength of LSS practices to achieve company’s quality goals. Moreover, this study will serve as a basis for future LSS scholars, providing them with valuable insights and directions for future research.

This paper develops a conceptual LSS framework that captures the integrated nature of two methodologies and provides empirical evidence that supports the positive influence of LSS practices on quality performance; hence, it contributes to the growing body of LSS literature in both theoretical and empirical sense.

This study aims to show the effectiveness and applicability of artificial intelligence applications in the measurement and evaluation of university services. Universities can gain competitive advantage through providing their students with quality services in various aspects, such as bookstores, dormitories, recreation centers as well as cafeterias. Among these facilities, university cafeterias are places where students spend a significant amount of time. Therefore, this study aims to integrate artificial intelligence application in the evaluation of university cafeteria services based on students' perceptions with two-stage structural equation modeling (SEM) and artificial neural network (ANN) approach.

An artificial intelligence based SEM-ANN hybrid approach was used to determine the factors that have significant influence on student satisfaction, sufficiency-of-services and likelihood-of-recommendation. Data were collected from 373 students through a face-to-face questionnaire. Initially, four service quality dimensions were attained through factor analysis. Then, hypotheses, which were determined via literature review, were tested through SEM-ANN hybrid approach.

Incorporating the results of SEM analysis into the ANN technique resulted in superior models with good prediction performance. Based on four ANN models created and ANN sensitivity analyses conducted, significant predictors of satisfaction, sufficiency, reliability and recommendation are determined and ranked.

Prior studies have assessed service quality using traditional techniques, whereas, this study integrates artificial intelligence in the assessment of higher-educational institutions' services quality. Also, as a distinction from previous studies, this study ranked importance levels of predictor variables through ANN sensitivity analysis.

The aim of this paper is to present a research framework for the green maintainability of buildings. This study makes the case for the development of a new concept called “green maintainability”. The paper also identifies and discusses the knowledge gap concerning green facilities management (FM). As an integral part of green FM, the economic, environmental and social impacts and opportunities of green maintainability throughout the total life cycle of the facility are also highlighted.

The little attention paid to the maintainability of green buildings has resulted in losses of lives due to occupational health and safety hazards as well as high operation and maintenance costs. To address this issue, this study has conducted a literature review to determine the relevant background knowledge and provides a conceptual framework that will aid in conceptualizing the green maintainability of buildings and the development of a research framework for the furtherance of this concept.

This paper finds that there is little research on the maintainability of green buildings, and the studies about the maintainability of green features are nonexistent in current research. This study confirms the knowledge gap of this little-researched area and draws from it the formulation of a research framework for the green maintainability of buildings to ensure green FM. Emerging literature on green practices and methods is currently receiving attention from academia, as well as building and construction practitioners, and can valuably contribute to the existing theories, practices and methods concerning building maintainability and facilities management.

This study develops the novel concept of green maintainability, which integrates maintainability and green FM at the planning/design stage. The proposed research framework is the first attempt to investigate the green maintainability of different typologies of buildings and especially green building technologies.