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This study aims to analyze the impact of Artificial Intelligence (AI) and Machine Learning (ML) on heritage conservation and preservation, and to identify relevant future research trends, by applying scientometrics.

A total of 1,646 articles, published between 1985 and 2021, concerning research on the application of ML and AI in cultural heritage were collected from the Scopus database and analyzed using bibliometric methodologies.

The findings of this study have shown that although there is a very important increase in academic literature in relation to AI and ML, publications that specifically deal with these issues in relation to cultural heritage and its conservation and preservation are significantly limited.

This study enriches the academic outline by highlighting the limited literature in this context and therefore the need to advance the study of AI and ML as key elements that support heritage researchers and practitioners in conservation and preservation work.

Facility management gained profound importance due to the increasing complexity of different systems and the cost of operation and maintenance. However, due to the increasing complexity of different systems, facility managers may suffer from a lack of information. The purpose of this paper is to propose a new facility management approach that links segmented assets to the vital data required for managing facilities.

Automatic point cloud segmentation is one of the most crucial processes required for modelling building facilities. In this research, laser scanning is used for point cloud acquisition. The research utilises region growing algorithm, colour-based region-growing algorithm and Euclidean cluster algorithm.

A case study is worked out to test the accuracy of the considered point cloud segmentation algorithms utilising metrics precision, recall and F-score. The results indicate that Euclidean cluster extraction and region growing algorithm revealed high accuracy for segmentation.

The research presents a comparative approach for selecting the most appropriate segmentation approach required for accurate modelling. As such, the segmented assets can be linked easily with the data required for facility management.

This research aims to explore the role played by Ijara-Murabaha Sukuk in attracting foreign direct investment (FDI) that adheres to Shariah principles into Pakistan’s oil sector. It focuses on the difficulties faced by the country in terms of payment for oil procurement. It highlights the recent collaboration with ARAMCO, Saudi Arabia’s national oil company, to establish the Gwadar Refinery Project. This project aims to enhance oil production, reduce costs and increase storage capacity.

Data was collected from 379 investors who participate in Ijara-Murabaha Sukuk through a questionnaire designed to evaluate how trade finance solutions, sustainability practices, transparency measures and governance structures impact FDI that comply with Shariah principles. The study also considers the moderating role of market conditions on these factors. Smart PLS 4 software was used to analyze their influence on creating an environment conducive to Shariah-compliant FDI.

The findings reveal that if the company prioritizes shariah-compliant foreign direct investment over conventional due to underlying productive activities ensuring economic growth as well as strong compliance mechanisms ensuring transparency, the multifaceted challenges associated with oil procurement, circular deficit, foreign exchange reserves and transparency problems can be solved. The groundbreaking analysis from this study will guide the major stakeholders while developing policies to convert the most expensive and massive budget deficit sector into a contributing sector of the economy.

This is a pioneering study on the application of Ijara-Murabaha Sukuk to resolve the problem of circular deficit of oil sectors of Pakistan by issuing 51% Ijara Sukuk for enhancing the capacity for the storage of oil and producing the oil from imported crude oil. 49% murabaha sukuk for importing crude oil. Successful implementation of the Shariah-compliant ARAMCO project can open the door to foreign direct investment for Pakistan and the other third economies, meeting the “Reducing Poverty of SDGs.”

In the era of the circular economy, the economic growth of a country is highly dependent on the sustainable performance of the manufacturing sector. In today’s increasingly competitive world, it is important to constantly improve the manufacturing or service industry. Quality with quantity is a main characteristic, which helps a company stay in the competition. Flexibility and responsiveness to customer demands are very important for success. Generally, additional time is needed for setup caused by poor design of equipment. At this point, the terms continuous process improvement and single-minute exchange of dies (SMED) as an approach of lean manufacturing come into play. Lean manufacturing system has been identified as an approach for improving the performance of the process and product.

In this paper, high setup time is considered as major problem in the industry and a major cause and effect for high setup time was found. On the basis of the literature review and experts’ opinions, four categories of barriers, namely method, manpower, machine and tools are identified. In this study, a hybrid approach comprising of the analytic hierarchy process (AHP) and graph theoretic approach (GTA) has been used. First, prioritization of different categories of barriers by AHP has been done, and second, GTA has been applied for finding the barriers' intensity index. Based on this study, machine and manpower barriers have emerged as major hurdles in the high setup time of machine. The proposed framework will help organizations quantify barriers in high setup time in different manufacturing processes, thereby developing effective strategies for sustainable production.

Findings of this research will contribute to ensuring sustainable competitive advantages, but it has some limitations. Development of the permanent matrix equation for barriers of high setup time is complex and lengthy when barriers are more in number. Absolute and relative values considered while quantifying the intensity of barriers are based on experts’ opinions, which may be inconsistent. In spite of these limitations, organizations can use an illustrated approach to quantify the barriers, thereby developing strategies for successful implementation of high setup time for making them sustainable in the global market. Organizations can also benchmark their sustainability preparedness with the best in the industry. As a future scope of study, high setup time can be reduced by using SMDE technology can be further validated through an empirical and case-based approach to generalize the findings.

Authors remain confined only to setup time. The approach is generalizable and can be extended in other areas. As a future scope of study, high setup time can be reduced by using single minute die exchange technology and can be further validated through an empirical and case-based approach to generalize the findings.

The study guides and facilitates researchers and practitioners in using the most appropriate techniques such as AHP and GTA for empirical studies and in developing, modifying and/or reviewing application frameworks for production. It also guides implementation experience regarding high setup time by using advanced techniques such as single point die exchange (SMDE), which can be beneficiary for both developing and developed country contexts. Industries can accelerate implementation by understanding and using most important AHP, GTA and SMDE techniques.

Lean manufacturing system has been identified as an approach for improving the performance of the process and product. A lean manufacturing system is part of corporate culture, like tools and approaches. High setup time can be classified as waste for the company. Reduction in time is a direct way to increase the productivity and profit. Therefore, there is a need to reduce the time by using some new lean methodology. In global industry, different techniques are used for reduction of time.

Organisations are looking for a concept that can solve traditional as well upgraded production problems with current resources and technology, and this can be addressed by integration of lean six sigma (LSS) with Industry 4.0 (I4.0) technologies. This reduces complexity in the manufacturing process through digital technologies. Cyber physical system (CPS) is considered as primary I4.0 technology with which all other technologies are associated to extend. CPS can integrate with other prevailing manufacturing approaches like lean, LSS and so on. LSS, on the other hand, is a team-focussed performance improvement strategy which is widely used by the industries to identify problems, eliminate waste to meet customer requirements. The study aims at analysis of challenges for LSS and CPS integration.

Integrating LSS and CPS will solve both traditional and modern manufacturing problems. To integrate these technologies, organisational requirements need to be assessed. These requirements are posed as challenges in this study. Their priority weights are analysed, and challenges are prioritised using fuzzy Combinative Distance-based Assessment (CODAS) method. Sensitivity analysis is employed to assess the robustness of the results.

The result of this study enables top management to integrate LSS and CPS. In this study, 20 challenges were identified, and they are assessed to compute their relative assessment score. Requirement of new tools and methods with 0.6 score ranks first followed by interplay with big data and requirement of new communication protocol. The result highlighted the need for integration of LSS and CPS, proper utilisation of information and communication technologies, and cyber security management as the main impediments that need to be addressed to implement CPS in an LSS environment.

The analysis of challenges of LSS and CPS integration using MCDM tool is the original contribution of the authors.

The role of intermediate urban centers (IUCs) (like towns/small cities/rural counties) between large cities and villages in leading urbanization has been increasingly highlighted. This article conceptually and empirically examines what types of industrial agglomeration (specialized or diversified agglomeration) of rural county in China would provide a more inclusive and efficient local labor market for rural workers to be inclusively urbanized.

We employ a three-stage labor supply model to theoretically generalize the decisions of rural workers to migrate to large city, to undertake nonfarm jobs in rural counties and the length of nonfarm jobs. Then, combining three national-level datasets of China (National Economic Census (NEC), China Household Income Project (CHIP) and the China county statistical yearbook), we explore how the type of industrial agglomeration in a rural county affects the labor supply decision of rural workers.

We show that rural workers in rural counties with higher level of industrial specialization are more likely to: (1) work locally than migrating to large cities; (2) find nonfarm jobs by themselves instead of relying on social networks (3) find a more stable and formal nonfarm job. These effects are significant when rural counties specialize in industries that they have local comparative advantages compared to large cities. This work provides insights into achieving inclusive urbanization by developing industry specialization in rural counties in China, which may also be useful for other developing countries.

First, the conceptual framework of this paper extends the basic model of rural-urban migration longstanding in the literature, to a multi-choice and three-stage labor supply model. Second, we empirically quantify the industrial structure of rural counties using unique dataset, which has been emphasized in the development economics literature but neglected due to data limitations. Third, this paper expands our understanding of the role of rural counties in inclusive urbanization and contributes to the future development of the county-led urbanization policies.

The presentation refers to simulations of magnetization processes of the spring-exchange magnetic composites containing magnetically soft and ultra-high coercive phases. In particular, the aim of this study is to investigate the possibility of reducing expensive rare earth (RE) in the so-called neodymium magnets and improving their efficiency.

In order to model hysteresis loops, a special disorder-based Monte Carlo procedure, suitable for irregular geometry of the composites, was applied. The chosen system parameters were defined in order to model Nd2Fe14B/Fe composites.

The results suggest potential for optimizing hard magnetic composites. Magnetization curve parameters are sensitive to grain coupling and easy magnetization axis ordering. Strong coupling for a single-phase hysteresis loop is unachievable for grains above a certain size, i.e. found to be a few hundred nanometers. Considering these factors and their interdependencies, it’s possible to enhance the |BH|max parameter or reduce the RE content.

The research was carried out using computer simulations, which by their nature are only approximations of physical processes. The next stage of research is to produce the described composites and test their actual properties.

The research enhances permanent magnets, boosting efficiency in technologies like wind turbines and electric motors, indirectly benefiting the environment. It also reduces RE elements in magnets for environmental, economic and political gains.

The unique approach is to consider the random orientation of the magnetic anisotropy of the hard magnetic grains, which is close to real powder composites. The results provide valuable guidance for the production process of permanent magnets.

We explore the intersection of Catholic social teaching (CST) and entrepreneurship studies which has seemingly evaded scholars’ attention.

We integrate and expand upon prior work to explicate an integrative framework for examining CST and entrepreneurship studies.

We articulate the mechanisms through which CST and entrepreneurship studies may extend our understanding of the economic paradigm of entrepreneurship studies.

We explicate the economic paradigm of entrepreneurship studies and present the key reasons for Catholicism’s and CST’s exclusion to demonstrate why this is unjustified. Beyond expounding what we mean by CST, we extend the economic paradigm by an application to show why the economic paradigm is flawed and call for more CST-focussed entrepreneurship studies.

This paper aims to highlight how the six sigma methods helped the medical equipment manufacturing company in finding and analysing the root causes that lead to the reduction in production rate, rejection rates, quality and other major causes that lead to the reduction in productivity of the blood bags manufacturing unit.

Given the critical nature of blood bag manufacturing Six Sigma was chosen as the primary methodology for this research since Six Sigma’s data-driven approach provides a structured framework to identify, analyse and rectify inefficiencies in the production processes. This study proposes the Six Sigma DMAIC (D-Define, M-Measure, A-Analyse, I-Improve, C-Control) encompassing rigorous problem definition, precise measurement, thorough analysis, improvement and vigilant control mechanisms for effectively attaining predetermined objectives.

The paper demonstrates how the Six Sigma principles were executed in a blood bag manufacturing unit. After a detailed and thorough data analysis, it was found that a total of 40 critical-to-quality factors under the five drivers such as Machine, Components, Inspection and Testing, People and Workspace were influential factors affecting the manufacturing of blood bags. From the study, it is identified that the drivers such as inspection and testing, components and machines contribute significantly to increasing productivity.

The paper offers valuable strategic insights into implementing Six Sigma methodologies within the specific context of a blood bag manufacturing unit. The Six Sigma tools and techniques used by the project team to solve issues within the blood bag manufacturing unit can be used for similar healthcare organizations to successfully deploy Six Sigma. The insights from this research might not be directly applicable to other manufacturing facilities or industries but can be used as a guiding reference for researchers and managers.

The current state of scholarly literature indicates a significant absence in the examination of Six Sigma methodologies designed specifically to improve production output in healthcare equipment manufacturing. This paper highlights the application of Six Sigma principles to enhance efficiency in the specific context of blood bag manufacturing.

The aim of this study is twofold. First, the study examines the effect of income inequality on conflicts in sub-Saharan Africa (SSA). Second, the study unveils the role of governance in income inequality – conflicts in sub-Saharan Africa (SSA).

The study adopts the ordinary least square estimation technique (OLS) as the baseline model. However, given that so many panel data models exhibit some form of cross-sectional and temporal dependence, the study also adopts the Driscoll–Kraay cross-sectional and spatial-consistent covariance matrix estimator.

The study finds that income inequality fuels conflicts in SSA. Similarly, the results show that an increase in the quality of governance reduces conflicts. Importantly, the result shows that the quality of governance mitigates the negative effects of income inequality on conflicts in SSA. The research and policy implications are discussed.

The study examines the role governance in income inequality – conflicts nexus in SSA.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2024-0055