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The study analysed the aerospace industry, a traditionally important sector for the topic of risk management, from three complementary perspectives: the supply chain risks present in the sector, the mitigation strategies adopted to face them, and the characteristics (dimensions) observed in the SCRM process of aerospace companies.

The research employed a quali–quantitative method: a survey was carried out, followed by interviews with professionals from companies belonging to different tiers of aerospace supply chains. Interviews helped to interpret the survey data and understand in more detail risk management in aerospace companies.

The study presents a panorama of the aerospace industry in terms of risk management. The sector’s turbulent environment is described as well as the strategies to prevent, minimise or postpone the impact of supply chain risks. In particular, ten dimensions that have been identified in the SCRM process of aerospace firms are discussed. These characteristics influence the objectives of this process and are related to resources, roles and responsibilities, incentives, development of competences and skills, scope (internal and external) and approaches to integrate decisions and actions in the context of the supply chain.

Articles that address the SCRM process usually focus on the process steps, whereas this study investigated dimensions that transcend these steps but whose discussion in the literature is still fragmented. It also analysed a reference sector for the topic from a broader perspective than others available in the literature (supply chain risks, mitigation strategies and characteristics of the SCRM process). Supply chain members with relationships with each other were investigated, a desirable approach for SCRM but still under-explored. The study also answers calls for industry-specific studies and research on emerging countries.

The purpose of the study is to examine how risk factors contribute to the occurrence of defects in a process. By analyzing these risk factors in relation to process quality, the study aims to help organizations prioritize their resources and efforts toward addressing the most significant risks. These challenges, integrated with the emerging concept of Quality 4.0, necessitate a comprehensive risk assessment technique.

Fuzzy logic integrated with an analytic network process is used in the process failure mode and effects analysis for conducting risk identification and assessment under uncertainty. Through a mathematical model, the linkage of risk with Six Sigma is established and, finally, a value–risk matrix is developed for illustrating and analysing risk impact on process quality.

A case study on fused filament fabrication demonstrates the proposed methodology’s applicability. The results show its effectiveness in assessing risk factors’ impact on Six Sigma metrics: defects per million opportunities/sigma level.

By integrating qualitative assessments and leveraging available data, this approach enables a more comprehensive understanding of risks and their utilization for an organization’s quality improvement initiatives.

This approach establishes a risk-centric Six Sigma assessment method in accordance with the requirement of ISO 9001:2015 and in the context of Quality 4.0.

This paper aims to provide insight on internal Shariah audit change process in Islamic banking institution using sociology of translationin and the identification of specific Islamic legal maxim (ILM).

This paper gathered findings using qualitative approach where a single case study was selected. The study began with a preliminary study to assist the selection of the case study and later two phases of interviews done at the institution selected as the case study.

This paper has provided insights into the internal Shariah audit practices change using sociology of translation that incorporated ILM as the basis to strengthen the Islamic banking operations by achieving maqasid al-Shariah (MS). The findings of this paper provide distinguished insight on internal Shariah audit change process and ILM. The significance of this study is that a new contribution through exploring the viewpoints of the perception that satisfying the minimum legal requirements of Shariah compliance may not be sufficient for proper Shariah audit in IBIs. Therefore, the existence of ILM within a change process serves as a basis for best practices to be able to achieve MS through the means (wasa’il) used in realising IBIs’ objectives.

The application of ILM to internal Shariah audit change process that would guide Muslim auditors to be in line with Islamic principles. This paper focuses on the application of ILM to the Shariah audit practices changes as ILM embodied ethical value to the general concept of maslahah (well-being) under MS in the period of post-COVID-19.

Motivated by the severe impact of global supply chain disruptions and the lack of understanding of supply chain resilience from an SME exporter perspective in the international marketing literature, this paper sets out to explore how SME exporters achieve resilience through strategic choices related to sourcing and manufacturing during global disruptions.

The study adopts a qualitative, multiple-case-studies approach to identify the key strategic drivers and contextual factors influencing SME exporters’ supply chain resilience. Our study adopted an SME exporter perspective and featured an unprecedented global supply chain disruption context. New Zealand (NZ) was chosen as the key home country context for the participants of this study. Five NZ SME exporters were selected for our case studies.

This study redefines buffering, bridging and a mixed strategy for an SME exporter facing global supply chain disruptions. SME exporters with high situational control are likely to pursue a buffering strategy that reduces their resource dependence on foreign suppliers and their reliance on information support from these suppliers. In contrast, when the firm perceives little control over the supply chain, it will decide upon a bridging strategy that aims to build solid relationships with supply chain partners. Exporters opt for a mixed strategy when they do not see themselves clearly in high or low situational control.

As global disruptions arise and evolve, supply chain uncertainty and exporters’ sense of situational control manifest differently across industries, product lines, markets and sourcing countries. It is essential to understand that firms can choose a mixed strategy based on these supply chain conditions. While our study was fortuitously timed, conducting multi-country studies could provide more comparative insights that transcend national borders. Additionally, our study did not examine organizational and capability-based factors. Future research may benefit from exploring how an SME exporter develops strategic capabilities to achieve resilience over its lifetime.

Businesses see survival as the most pivotal concern during a global supply chain disruption. Many companies have had to make on-the-spot decisions about whether they should shift or redesign their supply chains in the middle of a global disruption. There is no “best strategy” for an SME exporter to take. Rather, managers should make strategic decisions based on how much control or influence they have over a particular part of their supply chain. The level of control is determined by the SME exporter’s overall resource dependencies and information needs in particular parts of their supply chain.

We adopt resource dependence theory and information processing theory to guide our study and place exporters' situational control in the centre of drivers to firms' strategic choices during global disruptions. We make a novel attempt to incorporate the contextual conditions of the COVID-19 pandemic into the theorization of supply chain resilience. We make managerial recommendations to help SME exporters navigate global supply chain disruption challenges.

Recently, financial inclusion promoters have observed that financial literacy is a vital tool for financial inclusion growth, especially among the poor who are considered financially illiterate. The purpose of this paper is to look at the role of Islamic financial literacy (IFL) and inclusion in improving the performance of micro, small and medium enterprises (MSMEs) in Indonesia.

This study uses questionnaire data collected as many as 197 MSMEs. This study was analyzed using structural equation modeling approach to test the hypothesis.

The results show that IFL is an important variable to increase Islamic financial inclusion. The results also show that both have a significant influence in developing the MSME sector business.

This research is not without limitations. This study only adopted a sample in one Province in Indonesia with focus on creative economy sector and some others sectors located in the province of Riau, therefore ignoring suburban and urban areas in Indonesia. Therefore, future studies using a cross-sectional research design are feasible. In addition, this study only uses quantitative data, so that qualitative research with key informant interviews can be considered for further research.

The findings of this study enlighten policymakers, managers of financial institutions and advocates of financial literacy and inclusion about the importance of improving the performance of MSMEs. As a policy recommendation, this study suggests that Islamic policy makers and financial institutions should play a proactive role in increasing service outreach and providing the regulatory environment needed for MSMEs given the important role MSMEs play in the Indonesian economy.

This study combines functional components (behaviors and attitudes) and nonfunctional measures (knowledge and skills) of financial literacy and financial inclusion in explaining the performance of MSMEs. Thus, this research is an initial effort to explain financial literacy and inclusion on the performance of MSMEs.

The spatial–temporal conflicts in the construction process of concrete arch dams are related to the construction quality and duration, especially for pouring blocks with a continuous high-strength and high-density construction process. Furthermore, the complicated construction technology and limited space resources aggravate the spatial–temporal conflicts in the process of space resource allocation and utilization, directly affecting the pouring quality and progress of concrete. To promote the high-strength, quality-preserving and rapid construction of dams and to clarify the explosion moment and influence degree of the spatial–temporal conflicts of construction machinery during the pouring process, a quantification method and algorithm for a “Conflict Bubble” (CB) between construction machines is proposed based on the “Time–Space Microelement” (TSM).

First, the concept of a CB is proposed, which is defined as the spatial overlap of different entities in the movement process. The subsidiary space of the entity is divided into three layered spaces: the physical space, safe space and efficiency space from the inside to the outside. Second, the processes of “creation,” “transition” and “disappearance” of the CB at different levels with the movement of the entity are defined as the evolution of the spatial–temporal state of the entity. The mapping relationship between the spatial variation and the running time of the layered space during the movement process is defined as “Time–Space” (TS), which is intended to be processed by a microelement.

The quantification method and algorithm of the CB between construction machinery are proposed based on the TSM, which realizes the quantification of the physical collision accident rate, security risk rate and efficiency loss rate of the construction machinery at any time point or time period. The risk rate of spatial–temporal conflicts in the construction process was calculated, and the outbreak condition of spatial–temporal conflict in the pouring process was simulated and rehearsed. The quantitative calculation results show that the physical collision accident rate, security risk rate and efficiency loss rate of construction machinery at any time point or time period can be quantified.

This study provides theoretical support for the quantitative evaluation and analysis of the spatial–temporal conflict risk in the pouring construction process. It also serves as a reference for the rational organization and scientific decision-making for pouring blocks and provides new ideas and methods for the safe and efficient construction and the scientific and refined management of dams.

Despite efforts to improve safety management practices in industrial companies, major accidents seem to be inevitable. Many accidents still occur because companies are unable to learn from past occurrences due to ineffective incident and accident learning processes. This study proposes a learning-based framework for industrial accidents investigation and contributes to accident prevention research.

The proposed learning process includes the analysis of the industrial accident using the Event Tree Analysis (ETA) method, capitalisation of causative factors using the Swiss Cheese Model (SCM), and finally modelling the relationships among the accident causative factors and analysing their causality using the Fuzzy Cognitive Mapping (FCM) technique and running learning scenarios.

The proposed learning process was applied to an industrial accident, and the results showed that human unsafe behaviours and unsafe supervision were the principal causative factors of the blowout accident.

The proposed learning-based framework provides a structured approach for oil and gas companies to systematically analyse and learn from past accidents, enhancing their prevention strategies. Theoretically, the framework bridges the gap between theory and practice by demonstrating how established accident analysis methods can be combined and applied in a real-world industrial context.

The proposed learning process combines accident analysis and investigation techniques with simulations for an in-depth and robust learning-based framework for accident prevention.

A qualitative approach based on grounded theory was utilized, with data collected through 26 semi-structured interviews with social entrepreneurs. Alas’s Triangular Model provided the framework for data analysis and interpretation.

This study explores how Hong Kong social enterprises approached crisis and change management during the COVID-19 pandemic, examining their resilience-building strategies.

The pandemic triggered an existential crisis for many social enterprises, causing severe revenue losses. However, strong leadership and cultures based on social mission enabled resilience. Enterprises demonstrated agility by rapidly transitioning operations online and establishing partnerships. Technology adaptation and social innovation were pivotal to sustaining impact.

As the sample comprises enterprises that survived the pandemic, insights into failed enterprises are lacking. Comparative analysis could illuminate differences in crisis response between successful and unsuccessful cases.

The study’s practical implications suggest that social enterprises should focus on developing flexible crisis management plans, cultivating purposeful leadership, embracing digital transformation, strengthening collaborative networks and prioritizing organizational learning to effectively navigate crises while staying true to their social missions.

Findings demonstrate how shared values and cultures grounded in purpose can anchor organizations amidst upheaval, fostering resilience. This underscores the role of social enterprises in modeling responsiveness to societal needs.

While research has examined social enterprises’ vulnerability in crises, investigation into their crisis management practices is limited. This study enriches understanding of how social enterprises effectively navigate turbulence.

The purpose of this study is to present a methodical procedure on how to prepare event logs and analyse them through process mining, statistics and visualisations. The aim is to derive roots and patterns of quality deviations and non-conforming finished products as well as best practice facilitating employee training in the food processing industry. Thereby, a key focus is on recognising tacit knowledge hidden in event logs to improve quality processes.

This study applied process mining to detect root causes of quality deviations in operational process of food production. In addition, a data-ecosystem was developed which illustrates a continuous improvement feedback loop and serves as a role model for other applications in the food processing industry. The approach was applied to a real-case study in the processed cheese industry.

The findings revealed practical and conceptional contributions which can be used to continuously improve quality management (QM) in food processing. Thereby, the developed data-ecosystem supports production and QM in the decision-making processes. The findings of the analysis are a valuable basis to enhance operational processes, aiming to prevent quality deviations and non-conforming finished products.

Process mining is still rarely used in the food industry. Thereby, the proposed method helps to identify tacit knowledge in the food processing industry, which was shown by the framework for the preparation of event logs and the data ecosystem.

Unlocking the potential of Big Data Analytics (BDA) has proven to be a transformative factor for the Architecture, Engineering and Construction (AEC) industry. This has prompted researchers to focus attention on BDA in the AEC industry (BDA-in-AECI) in recent years, leading to a proliferation of relevant research. However, an in-depth exploration of the literature on BDA-in-AECI remains scarce. As a result, this study seeks to systematically explore the state-of-the-art review on BDA-in-AECI and identify research trends and gaps in knowledge to guide future research.

This state-of-the-art review was conducted using a mixed-method systematic review. Relevant publications were retrieved from Scopus and then subjected to inclusion and exclusion criteria. A quantitative bibliometric analysis was conducted using VOSviewer software and Gephi to reveal the status quo of research in the domain. A further qualitative analysis was performed on carefully screened articles. Based on this mixed-method systematic review, knowledge gaps were identified and future research agendas of BDA-in-AECI were proposed.

The results show that BDA has been adopted to support AEC decision-making, safety and risk assessment, structural health monitoring, damage detection, waste management, project management and facilities management. BDA also plays a major role in achieving construction 4.0 and Industry 4.0. The study further revealed that data mining, cloud computing, predictive analytics, machine learning and artificial intelligence methods, such as deep learning, natural language processing and computer vision, are the key methods used for BDA-in-AECI. Moreover, several data acquisition platforms and technologies were identified, including building information modeling, Internet of Things (IoT), social networking and blockchain. Further studies are needed to examine the synergies between BDA and AI, BDA and Digital twin and BDA and blockchain in the AEC industry.

The study contributes to the BDA-in-AECI body of knowledge by providing a comprehensive scope of understanding and revealing areas for future research directions beneficial to the stakeholders in the AEC industry.