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The purpose of this paper is to investigate how successful lean six sigma (LSS) manifests in the Australasian (Australian and New Zealand) context relative to the context in the USA in terms of LSS project definition, structure and practices.

In-depth investigation through case studies – 12 Australian/New Zealand cases and 4 US cases – on the implementation mechanisms of successful LSS initiatives.

A significant difference was found between Australasian and US definitions of an LSS project. However, firms in both regions followed similar project selection, initiating and execution practices. LSS reporting structures were found to be well-established in US organizations, but none of the Australasian organizations were found to be equipped with such a structure, although the effectiveness of LSS implementation success remained unaffected.

Sufficient uniformity of LSS was found across two regions implying its usefulness/generalizability, but the findings are based only on 12 cases.

The paper provides the groundwork to develop a unique LSS model for Australasian organizations to improve processes in an effective and efficient manner.

There is increasing interest in the connection between Industry 4.0 (I4.0) and operational excellence approaches; however, studies on the integration between Six Sigma (SS) and I4.0 have been absent from the literature. Integration with I4.0 technologies can maximize the positive effects of SS. The purpose of this study is to understand what types of relationships exist between SS and I4.0 and with I4.0's technologies, as well as the benefits derived from this integration and future directions for this field of study.

A Systematic Literature Review (SLR) was carried out to analyze studies about connections between I4.0 technologies and SS. SLR analyzed 59 articles from 2013 to 2021 extracted from the Web of Science and Scopus databases, including documents from journals and conferences.

The SLR identified relationships between SS and several I4.0 technologies, the most cited and with the greatest possibilities of relationships being Big Data/Big Data Analytics (BDA) and Internet of Things (IoT). Three main types of relationships were identified: (1) support of I4.0 technologies to SS; (2) assistance from the SS to the introduction of I4.0 technologies, and, to a lesser extent; (3) incompatibilities between SS and I4.0 technologies. The benefits are mainly related to availability of large data sets and real-time information, enabling better decision-making in less time.

In addition, the study can help managers to understand the integration relationships, which may encourage companies to adopt SS/Lean Six Sigma (LSS) in conjunction with I4.0 technologies. The results also drew attention to the incompatibilities between SS and I4.0 to anticipate potential barriers to implementation.

The study focuses on three previously unexplored subjects: the connection between SS and I4.0, the existing relationships with different technologies and the benefits resulting from the relationships. In addition, the study compiled and structured different types of relationships for SS and I4.0 and I4.0's technologies, identifying patterns and presenting evidence on how these relationships occur. Finally, exposes current trends and possible research directions.

Despite differing strategies towards environmental sustainability in developed and developing nations, the manufacturing sector in these regional domains faces substantial environmental issues. The purpose of this study is to examine the green-lean-six sigma (GLSS) enablers and outcomes for enhancing environmental sustainability of manufacturing firms in both, a developed and developing country context by using an environment-centric natural resource-based view (NRBV).

First, a framework of GLSS enablers and outcomes aligned with the NRBV strategic capabilities is proposed through a systematic literature review. Second, this framework is used to empirically investigate the GLSS enablers and outcomes of manufacturing firms through in-depth interviews with lean six sigma and environmental consultants from New Zealand (NZ) and Pakistan (PK) (developed and developing nations).

Analysis from both regional domains highlights the use of GLSS enablers and outcomes under different NRBV capabilities of pollution prevention, product stewardship and sustainable development. A comparison reveals that NZ firms practice GLSS to comply with environmental regulatory requirements, avoid penalties and maintain their clean-green image. Conversely, Pakistani firms execute GLSS to reduce energy use, satisfy international customers and create a green image.

This paper provides new insights on GLSS for environmental sustainability which can assist industrial experts and academia for future strategies and research.

This is one of the early comparative studies that has used the NRBV to investigate GLSS enablers and outcomes in manufacturing firms for enhancing environmental performance comparing developed and developing nations

This research paper aims to develop and validate an enhanced business process improvement methodology (EBPIM) by integrating the DMAIC (define, measure, analyze, improve and control) and the comprehensive business process management (CBPM) methodologies.

A systematic literature review and analysis were conducted to prove the novelty of the research approach and identify the similarities, differences, strengths and weaknesses of the DMAIC and the CBPM methodologies. The EBPIM was proposed based on the analysis results. Then, a focus group approach was used to evaluate and validate the methodology.

The EBPIM consists of nine activities: preparation, selection, description, quantification, modeling, enactment, improvement opportunities selection, analysis and improvement and monitoring. The proposed methodology adopted the systematic and structured process of the DMAIC methodology by having one tollgate between every two activities to check the progress and authorize the team to go to the next activity. At the same time, it has the ability of the CBPM methodology to enhance the interaction between human activities and business process management systems (BPMS).

The EBPIM was evaluated and validated by a focus group of academic professors. However, the main limitation of the proposed methodology is that it is still theoretical and needs to be empirically tested. Therefore, future work will focus on testing the EBPIM in different industries and organization sizes.

From the theoretical perspective, the proposed methodology adds value to the knowledge in the scope of business processes improvement methodologies (BPIMs) by integrating the DMAIC and the CBPM methodologies. It takes advantage of and combines the strengths of the DMAIC and CBPM methodologies. From the practical perspective, the proposed methodology presents a valuable tool that can facilitate the organization’s mission to improve the areas that need improvement using a systematic improvement methodology that will effectively enhance organizational performance (OP).

The BPIMs literature analysis proved that most of the reviewed methodologies could not support all phases of the business process improvement (BPI) activities. It was concluded that integrating the DMAIC and the CBPM methodologies is a novel approach. The proposed methodology will enhance the efficiency of both methodologies, fill the gaps that may exist in both of them and lead to better results in terms of BPI.

This study investigates the flow and heat transfer in a magnetohydrodynamic (MHD) ternary hybrid nanofluid (HNF), considering the effects of viscous dissipation and radiation.

The transport equations are transformed into nondimensional partial differential equations. The local nonsimilarity (LNS) technique is implemented to truncate nonsimilar dimensionless system. The LNS truncated equation can be treated as ordinary differential equations. The numerical results of the equation are accomplished through the implementation of the bvp4c solver, which leverages the fourth-order three-stage Lobatto IIIa formula as a finite difference scheme.

The findings of a comparative investigation carried out under diverse physical limitations demonstrate that ternary HNFs exhibit remarkably elevated thermal efficiency in contrast to conventional nanofluids.

The LNS approach (Mahesh et al., 2023; Khan et al., 20223; Farooq et al., 2023) that we have proposed is not currently being used to clarify the dynamical issue of HNF via porous media. The LNS method, in conjunction with the bvp4c up to its second truncation level, yields numerical solutions to nonlinear-coupled PDEs. Relevant results of the topic at hand, obtained by adjusting the appropriate parameters, are explained and shown visually via tables and diagrams.

For some years now, Cameroon has seen a significant increase in its electricity demand, and this need is bound to grow within the next few years owing to the current economic growth and the ambitious projects underway. Therefore, one of the state's priorities is the mastery of electricity demand. In order to get there, it would be helpful to have reliable forecasting tools. This study proposes a novel version of the discrete grey multivariate convolution model (ODGMC(1,N)).

Specifically, a linear corrective term is added to its structure, parameterisation is done in a way that is consistent to the modelling procedure and the cumulated forecasting function of ODGMC(1,N) is obtained through an iterative technique.

Results show that ODGMC(1,N) is more stable and can extract the relationships between the system's input variables. To demonstrate and validate the superiority of ODGMC(1,N), a practical example drawn from the projection of electricity demand in Cameroon till 2030 is used. The findings reveal that the proposed model has a higher prediction precision, with 1.74% mean absolute percentage error and 132.16 root mean square error.

These interesting results are due to (1) the stability of ODGMC(1,N) resulting from a good adequacy between parameters estimation and their implementation, (2) the addition of a term that takes into account the linear impact of time t on the model's performance and (3) the removal of irrelevant information from input data by wavelet transform filtration. Thus, the suggested ODGMC is a robust predictive and monitoring tool for tracking the evolution of electricity needs.

The demand for healthcare innovation is increasing, and not much is known about how entrepreneurial firms search for and sell to customers in the highly regulated and complex healthcare market. Drawing on effectuation perspectives, we explore how entrepreneurial digital healthcare firms with disruptive innovations search for early customers in the healthcare sector.

This study uses a qualitative, longitudinal multiple-case design of four entrepreneurial Nordic telehealth firms. In-depth interviews were conducted with founders and senior managers over a period of 27 months.

We find that when customer buying conditions are highly flexible, case firms use effectual logic to generate customer demand for disruptive innovations. However, under constrained buying conditions firms adopt a more causal approach to customer search.

Managers need to gain a deep understanding of target buying environments when searching for customers. In healthcare sector markets, the degree of flexibility customers have over buying can constrain them from engaging in demand co-creation. In particular, healthcare customer access to funding streams can be a key determinant of customer flexibility.

We contribute to effectuation literature by illustrating how customer buying conditions influence decision-making logics of entrepreneurial firms searching for customers in the healthcare sector. We contribute to entrepreneurial resource search literature by illustrating how entrepreneurial firms search for customers beyond their networks in the institutionally complex healthcare sector.