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This paper presents Quick Changeover Design (QCD), which is a structured methodological approach for Original Equipment Manufacturers to drive and support the design of machines in terms of rapid changeover capability.

To improve the performance in terms of set up time, QCD addresses machine design from a single-minute digit exchange of die (SMED). Although conceived to aid the design of completely new machines, QCD can be adapted to support for simple design upgrades on pre-existing machines. The QCD is structured in three consecutive steps, each supported by specific tools and analysis forms to facilitate and better structure the designers' activities.

QCD helps equipment manufacturers to understand the current and future needs of the manufacturers' customers to: (1) anticipate the requirements for new and different set-up process; (2) prioritize the possible technical solutions; (3) build machines and equipment that are easy and fast to set-up under variable contexts. When applied to a production system consisting of machines subject to frequent or time-consuming set-up processes, QCD enhances both responsiveness to external market demands and internal control of factory operations.

The QCD approach is a support system for the development of completely new machines and is also particularly effective in upgrading existing ones. QCD's practical application is demonstrated using a case study concerning a vertical spindle machine.

Given the importance of credit rating agencies’ (CRAs) assessment in affecting international financial markets, it is useful for policymakers and investors to be able to forecast it properly. Therefore, this study aims to forecast sovereign risk perception of the main agencies related to Brazilian bonds through the application of different machine learning (ML) techniques and evaluate their predictive accuracy in order to find out which one is best for this task.

Based on monthly data from January 1996 to November 2018, we perform different forecast analyses using the K-Nearest Neighbors, the Gradient Boosted Random Trees and the Multilayer Perceptron methods.

The results of this study suggest the Multilayer Perceptron technique is the most reliable one. Its predictive accuracy is relatively high if compared to the other two methods. Its forecast errors are the lowest in both the out-of-sample and in-sample forecasts’ exercises. These results hold if we consider the CRAs classification structure as linear or logarithmic. Moreover, its forecast errors are not statistically associated with periods of changes in CRAs’ opinion of any sort.

To the best of the authors’ knowledge, this study is the first to evaluate the performance of ML methods in the task of predicting sovereign credit news, including not only the sovereign ratings but also the outlook and credit watch status. In addition, the authors investigate whether the forecasts errors are statistically associated with periods of changes in sovereign risk perception.

The objective of this research is to develop an solution to water management at the scale of buildings, through the technological resources. Automating analysis using 3D models helps increase efficiency in buildings during the operational phase, consequently promotes sustainability.

This study presents a methodology based on Design Science Research to automate water management at building scale integrating BIM-IoT-FM. Data from smart meters (IoT) and the BIM model were integrated to be applied in facilities management (FM) to improve performance of the building. The methodology was implemented in a prototype for the web, called AquaBIM, which captures, manages and analyzes the information.

The application of AquaBIM allowed the theoretical evaluation and practical validation of water management methodology. By BIM–IoT integration, the consumption parameters and ranges for 17 categories of activities were determined to contribute to fulfill the research gap for the commercial buildings. This criterion and other requirements are requirements met in order to obtain the AQUA-HQE environmental sustainability certification.

Traditionally, water management in buildings is based on scarce data. The practical application of digital technologies improves decision-making. Moreover, the creation of consumption indicators for commercial buildings contributes to the discussion in the field of knowledge.

This article emphasizes the investigation of the efficiency of use in commercial buildings using operational data and the use of sustainable consumption indicators to manage water consumption.

The objective of this systematic literature review (SLR) is to explore the current state of research in the field of household finance (HF). This study aims to summarize the existing research to highlight the importance of household finance in a nation’s economy. By exploring all conceptual and applied implications of HF, this study projects directions for future research to develop a comprehensive understanding of the subject.

This SLR is based on 112 articles published in peer-reviewed journals between 2006 and 2020 (Table 3). The methodology comprises five steps, namely, formulation of research questions, identification of studies, their selection and evaluation, analyses and syntheses and presentation of results.

The findings of this study show that studies on HF are gradually increasing worldwide with the USA registering the highest number of published research on the topic during the period under scrutiny. Notwithstanding the increasing attention and research on HF, empirical research in emerging economies is lagging. Additionally, this study finds that HF structure presents a perfect setting to understand how households compose their financial portfolio, make financial decisions and what factors influence their decisions.

This study is an SLR – an accurate and accepted method of reviewing available literature on a selected subject. However, the selection of inclusion and exclusion criteria depends on the researchers’ rationale which might lead to research bias. This should be considered an inherent limitation of SLR.

By synthesizing the contents of extant literature, this study presents important insights into HF. This study underlines the most discussed topics in the domain and identifies potential investigation areas. This study gives the knowledge of leading articles, authors and journals and informs scholars and academicians about the areas that need further investigation by portraying the complete picture of the subject in a systematic manner. Further, this study highlights that households make suboptimal financial decisions that affect their financial well-being. To reduce the adverse impacts of these decisions, policymakers and financial institutions must take steps to improve households’ use of formal financial markets. Household decisions can be reformed by enhancing consumers’ knowledge about financial products and services. Furthermore, households can be served better by offering customization in traditional financial products.

This study synthesizes the main findings of selected literature on HF. The expansion of studies on HF has generated the need to review the existing literature in a systematic manner. To the researchers’ best knowledge, this SLR is the first thorough study of available articles in the HF domain. This study presents the scope of future research by highlighting numerous aspects and functions of HF.

This study seeks to estimate union wage effect in the public and private sectors of Ghana, respectively. It also seeks to ascertain whether the union wage effect in the two sectors varies.

The authors use data from the Ghana Living Standards Survey 6 (GLSS 6, 2012/2013) and Ghana Labour Force Survey (GLFS, 2015). In terms of estimation technique, the authors employ the Blinder–Oaxaca decomposition technique to estimate union wage effect in public and private sectors, respectively.

The findings indicate that union wage effect in the public sector is positive and higher relative to that of the private sector.

The findings imply that strict enforcement of Section 82 of Labour Act 2003 (Act 651) will curb the political influence of public sector unions over their employer (Government).

This research paper has not been presented to any journal for publication and it is the authors' original work.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0045

The purpose of this study is to identify the association between environmental leadership (EL) and pro-environmental behaviour among the middle-level employees in iron and steel manufacturing companies. The study further emphasizes on mediation of the relationship by green rewards and green self-efficacy in EL and pro-environmental behaviour relationship, moderated by green training.

To find the reliability and validity of the model, confirmatory factor analysis was used. Pearson correlation was used to explore the relationship between variables. PROCESS macro of Hayes (2013) Model 14 was used to test mediation and moderated mediation.

EL influenced pro-environmental behaviour in middle-level employees. Green rewards and green self-efficacy mediated the relationship. Green training moderated the mediated relationship of green rewards and green self-efficacy between EL and pro-environmental behaviour.

This is a fresh contribution around EL and pro-environmental behaviour in iron and steel companies; however, there are studies available on this relationship, but the unique contribution of the study is studying EL in iron and steel companies and mediated moderated relationship by green rewards, self-efficacy and training. It is necessary for the organizations to develop environmental leaders to promote pro-environmental behaviour in employees across sectors.

This study aims to study the factors that drive non-users of digital banking services rendered by Islamic banks in Malaysia towards their adoption of digital services in the banking 4.0 era using the innovation diffusion theory (IDT), also known as the diffusion theory of innovation (DOI).

IDT theory and literature on intention to adopt digital bank services were reviewed in a bid to contribute to the factors that drive non-users to adopt digital banking.

The review suggests that the adoption of digital banking is determined not only by perceived relative advantage, and perceived compatibility but also by additional factors in IDT theory, which are technology self-efficacy and perceived expected benefits. On the contrary, perceived complexity does not turn out to be a factor of digital banking adoption.

Considering this paper in terms of the limited scope of the theory rendered and the context, it should be given proper attention when interpreting future outcomes when further investigations are brought into play in terms of population and sampling method.

This paper serves as a guide to ensure the better planning of non-users’ adoption factors related to Islamic bank customers in both theory and practice.

DOI is extended in the context of digital banking, as evidenced by empirical results, and literature shows that IDT integrated with the technology self-efficacy model is yet to be proposed in the digital banking adoption by Islamic bank customers. Additionally, variables, namely, perceived expected benefits and technology self-efficacy, are proposed in IDT’s existing model. Current findings will therefore serve as a relevant reference for digital technology specialists, policymakers, Islamic banks’ IT managers, academicians and future researchers.