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The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

This study aims to focus on how smartphone addiction impacts young consumer behavior related to mobile technology (i.e. the compulsive app downloading tendency). After a thorough literature review and following the risk and protective factors framework, this study explores factors that could mitigate its effects (resilience, family harmony, perceived social support and social capital).

The study used the covariance-based structural equation modeling approach to analyze data collected from 275 Generation Z (Gen Z) smartphone users in Spain.

Results suggest that resilience is a critical factor in preventing smartphone addiction, and smartphone addiction boosts the compulsive app downloading tendency, a relevant downside for younger Gen Z consumers.

Through the lens of the risk and protective factors framework, this study focuses on protective factors to prevent smartphone addiction and its negative side effects on app consumption. It also offers evidence of younger consumers’ vulnerability to smartphone addiction, not because of the device itself but because of app-consumption-related behaviors.

Business models (BMs) are becoming increasingly crucial for value creation in the healthcare sector. The study explores the conceptualization and application of BM concepts within the healthcare sector and investigates their evolution in emerging economies (EEs) and developed economies (DEs). This study aims to uncover these two contexts' shared characteristics and unique variances through a comparative analysis.

The paper systematically investigates and consolidates the literature on healthcare by employing the antecedents, decisions and outcomes (ADO) framework and finally examines 71 shortlisted articles published between 2003 and 2022.

The recognition of the BM within healthcare is increasing, both in EEs and DEs. EEs prioritize value creation and capture through cost efficiency, while DEs focus on innovation. Key theories employed include a resource-based view, the network theory and the theory of innovation. Case studies are commonly used as a methodology. Further research is needed to explore the decisions and outcomes of BMs.

The study adopts stringent filtration and keyword criteria, potentially excluding relevant research. Future researchers are encouraged to broaden their selection criteria to encompass a more extensive range of relevant studies.

Beyond comparing and highlighting gaps in BMs between EEs and DEs, benchmarking DE's healthcare business models (HBMs) helps healthcare organizations in EEs align their practices, mitigate risks and establish efficient healthcare systems tailored to their specific contexts. The study adopts stringent filtration and keyword criteria, potentially excluding relevant research. Future researchers are encouraged to broaden their selection criteria to encompass a more extensive range of relevant studies.

The study analyzes HBMs using an SLR framework perspective and provides practical implications for academicians and practitioners to enhance their decision-making.

In comparison to other countries, power generation in Sub-Saharan Africa is poor. The demand for power has surged in recent times and continues to increase at a fast rate. The public–private partnership (PPP) model has been identified as an option to address the challenges in the power sector. The purpose of this research paper is to critically explore the reasons for entering into PPP power projects in Ghana by the public and private parties.

Questionnaires were used to elicit responses from respondents using a two-round Delphi survey. From 60 respondents contacted in round one, 48 responses were obtained, and these 48 respondents further took part in round two. Mean score ranking was used to rank the reasons for entering into PPP power projects, while analysis of variance (ANOVA) was run to test significant difference in perceptions among the respondents.

From round 2 of the Delphi survey, the significant reasons for public sector entering into PPP power projects were as follows: achieving improved value for money, access to additional capital, increased certainty of projects and greater efficiency of project delivery services. For private sector, most significant reasons were as follows: obtaining of investment support, improvement in private sector’s international image and synergy with public sector. From ANOVA analysis, there were significant different perceptions among some of factors on the respondent profile variables and the reasons for entering into PPP power projects, while other factors did not have significant different perception.

Significant reasons for both public and private sectors identified would be incorporated by the government when PPP policy guidelines and laws are reviewed. This will aid in the effective implementation of PPP for power projects.

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

This research aims to examine the role of consumers' brand trust and attachment on advocacy intention before and after the occurrence of brand misconduct in retail banking. In addition, the influence of brand attachment on consumers' willingness to switch, advocate for and forgive brands is examined in a post-misconduct scenario.

Data were collected through a self-administered online survey questionnaire. A total of 304 valid and usable responses from Australian participants were analysed using IBM SPSS 27.0.

The findings reveal that brand attachment mediates the positive relationship between trust and advocacy intention. Furthermore, brand attachment (1) dilutes consumers' switching intention and (2) strengthens their willingness to forgive the bank after misconduct.

Results suggest that retail banks should create strong brand attachments with their consumers. In addition to brand trust, brand attachment will generate greater advocacy intention among consumers. Moreover, practitioners in retail banking can leverage brand attachment to mitigate the negative impact of brand misconduct.

To the best of the authors' knowledge, this study is the first to examine the impact of brand attachment on the consumer–bank relationship within the context of brand misconduct. The study is also unique in its analysis of the mediating role of brand attachment between brand trust and advocacy. This research further adds to the current literature by suggesting that strong and positive customer connections to the brand facilitate communication and marketing efforts after brand misconduct and that these are effective in maintaining consumer-bank relationship.

Supply chain vulnerability (SCV) analysis is vital for manufacturers globally because it creates a pathway for building resilient supply chains in uncertain environments. This study aims to identify drivers of SCV in the Indian manufacturing sector.

Sixteen drivers were identified from the literature review and followed by expert interviews. Interpretive structural modeling was used to determine the hierarchical structural relationship among identified SCV factors.

It was found that risk is not a board room agenda. Misaligned performance measures with incentives and lack of risk dashboard are the causal factors of SCV. Supply chain security, centralized production and distribution and lack of trust in the supply chain were driven factors.

This provides new insights to assess and prioritize initiatives for supply chain sustainability in terms of continuing business operations. The structural model provides a systemic view of SCV and helps reduce vulnerability.

The various quality improvement (QI) frameworks and maturity models described in the health services literature consider some aspects of QI while excluding others. This paper aims to present a concerted attempt to create a quality improvement maturity model (QIMM) derived from holistic principles underlying the successful implementation of system-wide QI programmes.

A hybrid methodology involving a systematic review (Phase 1) of over 270 empirical research articles and books developed the basis for the proposed QIMM. It was followed by expert interviews to refine the core constructs and ground the proposed QIMM in contemporary QI practice (Phase 2). The experts included academics in two academic conferences and 59 QI managers from the New Zealand health-care system. In-depth interviews were conducted with QI managers to ascertain their views on the QIMM and its applicability in their respective health organisations (HOs).

The QIMM consists of four dimensions of organisational maturity, namely, strategic, process, supply chain and philosophical maturity. These dimensions progress through six stages, namely, identification, ad-hoc, formal, process-driven, optimised enterprise and finally a way of life. The application of the QIMM by the QI managers revealed that the scope of QI and the breadth of the principles adopted by the QI managers and their HOs in New Zealand is limited.

The importance of QI in health systems cannot be overstated. The proposed QIMM can help HOs diagnose their current state and provide a guide to action achieving a desirable state of quality improvement maturity. This QIMM avoids reliance on any single QI methodology. HOs – using the QIMM – should retain full control over the process of selecting any QI methodology or may even cherry-pick principles to suit their needs as long as they understand and appreciate the true nature and scope of quality overstated. The proposed QIMM can help HOs diagnose their current state and provide a guide to action achieving a desirable state of quality improvement maturity. This QIMM avoids reliance on any single QI methodology. HOs – using the QIMM – should retain full control over the process of selecting any QI methodology or may even cherry-pick principles to suit their needs as long as they understand and appreciate the true nature and scope of quality.

This paper contributes new knowledge by presenting a maturity model with an integrated set of quality principles for HOs and their extended supply networks.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

Little is known about the determinants of supply chain finance (SCF) adoption among small and medium-sized enterprises (SMEs) in developing countries. This study aims to address this relevant research gap and hence, draws on the resource-based view and transaction cost economies to empirically investigate five factors that make SCF adoption practicable among SMEs in Ghana.

The approach involves a sample of 257 SME managers/owners and modelling via structural equations modelling.

All five factors (innovative capability, information sharing, inter- and intra-firm collaboration, external financing and trade process digitization) were found to impact positively and significantly on SCF adoption. The findings provide SME managers/owners with a research model which guides them on how to settle the SCF process.

This paper used a cross-sectional survey, which makes it impossible to access changes over time. In addition, the use of quantitative method limits respondents from expressing their feelings fully. Using a mixed or qualitative methodology will provide avenues for future research.

This paper offers a completive advantage for Ghanaian SMEs to strengthen their relationships while collaborating with each other. The findings suggest that by adopting SCF solutions, SMEs can optimize their liquidity and working capital. The factors underpinning SCF adoption are of incredible attractiveness for SME managers/owners to discover the relevant practice of SCF solutions. SMEs should adopt SCF strategies for improving their capability to respond promptly to transactions.

This paper is among the few papers that have examined these five factors in a developing economy context. The study also provides new understanding of the factors that influence SCF adoption in the context of a developing economy.