Search results

This study aims to identify research trends and technological evolution in the polymer three-dimensional (3D) printing process that can effectively identify the direction of technological advancement and progress of acceptance in both society and key manufacturing industries.

The Scopus database was used to collect data on polymer 3D printing papers. This study uses bibliometric approach along with network analytic techniques to identify and discuss the most important countries and their scientific collaboration, compares income groups and analyses keyword trends.

It was found that top research production results from heavy investments in research and development. The USA has the highest number of papers among the high-income countries. However, scientific production in the other two income groups is strongly dominated by China and India. Keyword analysis shows that countries with lower incomes in certain areas, such as composite and bioprinting, have fallen behind other groups over time. International collaborations were suggested as mechanisms for those countries to catch up with the current research trends. The evolution of the research field, which started with a focus on 3D printing processes and shifted to printed part designs and their applications, was discussed. The advancement of the research topic suggests that translational research on polymer 3D printing has been led mainly by research production from higher-income countries and countries with large research and development investments.

Previous studies have conducted performance analysis, science mapping and network analysis in the field of 3D printing, but none have focused on global research trends classified by country income. This study has conducted a bibliometric analysis and compared the outputs according to various income levels according to the World Bank classification.

The effectiveness of rhetorical structure is essential to communicate key messages in research articles (RAs). The interdisciplinary nature of library and information science (LIS) has led to unclear patterns and practice of using rhetorical structures. Understanding how RAs are constructed in LIS to facilitate effective scholarly communication is important. Numerous studies investigated the rhetorical structure of RAs in a range of disciplines, but LIS articles have not been well studied.

In this study, the authors encoded rhetorical structures to 2,216 articles in the Journal of the Association for Information Science and Technology covering a period from 2001 to 2018 with the approaches of co-word analysis and visualization. The results show that the predominant rhetorical structures used by LIS researchers follow the sequence of Introduction-Literature Review-Methodology-Result-Discussion-Conclusion (ILMRDC).

The authors' temporal examination reveals the shifts of evolutionary pattern of rhetorical structure in 2008 and 2014. More importantly, the authors' study demonstrates that rhetorical structures have varied greatly across research areas in LIS community. For example, scholarly communication and scientometrics studies tend to exclude literature review in articles.

The present paper offers a first systematic examination of how rhetorical structures are used in a representative sample of a LIS journal, especially from a temporal perspective.

Additive manufacturing also known as 3D printing is an evolving advanced manufacturing technology critical for the new era of complex machinery and operating systems. Manufacturing systems are increasingly faced with risk of attacks not only by traditional malicious actors such as hackers and cyber-criminals but also by some competitors and organizations engaged in corporate espionage. This paper aims to elaborate a plausible risk practice of designing and demonstrate a case study for the compromised-based malicious for polymer 3D printing system.

This study assumes conditions when a machine was compromised and evaluates the effect of post compromised attack by studying its effects on tensile dog bone specimens as the printed object. The designed algorithm removed predetermined specific number of layers from the tensile samples. The samples were visually identical in terms of external physical dimensions even after removal of the layers. Samples were examined nondestructively for density. Additionally, destructive uniaxial tensile tests were carried out on the modified samples and compared to the unmodified sample as a control for various mechanical properties. It is worth noting that the current approach was adapted for illustrating the impact of cyber altercations on properties of additively produced parts in a quantitative manner. It concurrently pointed towards the vulnerabilities of advanced manufacturing systems and a need for designing robust mitigation/defense mechanism against the cyber altercations.

Density, Young’s modulus and maximum strength steadily decreased with an increase in the number of missing layers, whereas a no clear trend was observed in the case of % elongation. Post tensile test observations of the sample cross-sections confirmed the successful removal of the layers from the samples by the designed method. As a result, the current work presented a cyber-attack model and its quantitative implications on the mechanical properties of 3D printed objects.

To the best of the authors’ knowledge, this is the original work from the team. It is currently not under consideration for publication in any other avenue. The paper provides quantitative approach of realizing impact of cyber intrusions on deteriorated performance of additively manufactured products. It also enlists important intrusion mechanisms relevant to additive manufacturing.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

This study reviews scholarly work in sustainable green logistics and remanufacturing (SGLR) and their subdisciplines, in combination with bibliometric, thematic and content analyses that provide a viewpoint on categorization and a future research agenda. This paper provides insight into current research trends in the subjects of interest by examining the most essential and most referenced articles promoting sustainability and climate-neutral logistics.

For the literature review, the authors extracted and sifted 2180 research and review papers for the period 2008–2023 from the Scopus database. The authors performed bibliometric and content analyses using multiple software programs such as Gephi, VOSviewer and R programming.

The SGLR papers can be grouped into seven clusters: (1) The circular economy facets; (2) Decarbonization of operations to nurture a climate-neutral business; (3) Green sustainable supply chain management; (4) Drivers and barriers of reverse logistics and the circular economy; (5) Business models for sustainable logistics and the circular economy; (6) Transportation problems in sustainable green logistics and (7) Digitalization of logistics and supply chain management.

In this review, fundamental ideas are established, research gaps are identified and multiple future research subjects are proposed. These propositions are categorized into three main research streams, i.e. (1) Digitalization of SGLR, (2) Enhancing scopes, sectors and industries in the context of SGLR and (3) Developing more efficient and effective climate-neutral and climate change-related solutions and promoting more environmental-related and sustainability research concerning SGLR. In addition, two conceptual models concerning SGLR and climate-neutral strategies are developed and presented for managers and practitioners to consider when adopting green and sustainability principles in supply chains. This review also highlights the need for academics to go beyond frameworks and build new techniques and instruments for monitoring SGLR performance in the real world.

This study provides an overview of the evolution of SGLR; it also clarifies concepts, environmental concerns and climate change practices, particularly those directed to supply chain management.

This paper aims to develop a comprehensive model on intra- and interpersonal emotion regulation (ER) in hospitality and tourism (H&T) service encounters.

A critical review and reflection of ER research from multiple disciplines was conducted. Methodologies appropriate for investigating ER were also reviewed.

A comprehensive framework was proposed to outline key influential factors, processes and consequences of intra- and interpersonal ER in service encounters in the H&T industry. Methodologies integrating advanced tools were suggested to measure complex and dynamic emotion generation and regulation processes in social interactions from a multimodal perspective.

The researchers developed a comprehensive conceptual model on both intra- and interpersonal ER based on a critical review of the most recent psychological research on ER. Various theoretical and methodological considerations are discussed, offering H&T scholars a solid starting point to explore dynamic emotion generation and regulation processes in complex social settings. Moreover, the model provides future directions for the expansion of ER theories, which have been mostly developed and tested based on laboratory research.

The proposed model addresses two critical issues identified in emotion research in the H&T field: the lack of a dynamic perspective and the neglect of the social nature of emotions. Moreover, the model provides a roadmap for future research.

This paper aims to give an oversight of what is being done by researchers in GIS and remote sensing (field) to explore minerals. The main objective of this review is to explore how GIS and remote sensing have been beneficial in identifying mineral deposits for easier and cost-effective mining.

The approach of this research used Web of Science to generate a database of published articles on the application of GIS and remote sensing techniques for mineral exploration. The literature was further digested, noting the main findings, adopted method, illustration and research scales.

When applied alone, each technique seems effective, but it is important to know that combining different methods is more effective in identifying ore deposits.

This paper also examined and provided possible solutions to both current and future perspective issues relating to the application of GIS and remote sensing to mineral exploration. The authors believe that the conclusions and recommendations drawn from case studies and literature review will be of great importance to geoscientists and policymakers.

Racism occurs in many ways and varies across countries, evolving and adapting to sociocultural history, as well as contemporary economic, political and technological changes. This chapter discusses the multilevel dimensions of racism and its diverse manifestations across multiracial societies. It examines how different aspects of racism are mediated interpersonally, and embedded in institutions, social structures and processes, that produce and sustain racial inequities in power, resources and lived experiences. Furthermore, this chapter explores the direct and indirect ways racism is expressed in online and offline platforms and details its impacts on various groups based on their intersecting social and cultural identities. Targets of racism are those who primarily bear the adverse effects. However, racism also affects its perpetrators in many ways, including by limiting their social relations and attachments, and by imposing social and economic costs. This chapter thus analyses the many aspects of racism both from targets and perpetrators' perspectives.

This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.

VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.

The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.

The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.

The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.

Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.