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Fabrication settings such as printing speed and nozzle temperature in fused deposition modeling undeniably influence the quality and strength of fabricated parts. As available market filaments do not contain any exact information report for printing settings, manufacturers are incapable of achieving desirable predefined print accuracy and mechanical properties for the final parts. The purpose of this study is to determine the importance of selecting suitable print parameters by understanding the intrinsic behavior of the material to achieve high-performance parts.

Two common commercial polylactic acid filaments were selected as the investigated samples. To study the specimens’ printing quality, an appropriate scaffold geometry as a delicate printing sample was printed according to a variety of speeds and nozzle temperatures, selected in the filament manufacturer’s proposed temperature range. Dimensional accuracy and qualitative surface roughness of the specimens made by one of the filaments were evaluated and the best processing parameters were selected. The scaffolds were fabricated again by both filaments according to the selected proper processing parameters. Material characterization tests were accomplished to study the reason for different filament behaviors in the printing process. Moreover, the correlations between the polymer structure, thermo-rheological behavior and printing parameters were denoted.

Compression tests revealed that precise printing of the characterized filament results in more accurate structure and subsequent improvement of the final printed sample elastic modulus.

The importance of material characterization to achieve desired properties for any purpose was emphasized. Obtained results from the rheological characterizations would help other users to benefit from the highest performance of their specific filament.

This study aims to give a glimpse of the existing blockchain applications across industries and add to a complete knowledge of the blockchain’s properties.

Systematic literature review is used as the research strategy for this investigation and other aspects of the preferred reporting items for systematic reviews and meta-analyses framework have been incorporated to create a scholarly publications evaluation of the blockchain-based application in the financial arena and its future. The research looks at 86 studies published between 2018 and 2022.

There has been a steady but noticeable increase in the study of blockchain’s potential in many application domains over the past few of years. This rising tendency illustrates the newness and potential of blockchain technology, as well as the increasing attention from academics. According to the findings, blockchain is an appropriate solution for processing transactions using cryptocurrencies; nevertheless, it still has significant technical issues and limits that require to be exploring and solving before it can be considered a viable option. It is therefore, necessary to have a high level of reliability for payments and confidentiality, in addition to maintaining the anonymity of nodes, to stop assaults and efforts to disrupt transactions in the blockchain.

This study has several important theoretical and practical implications. First, it adds to the body of knowledge on blockchain and Fintech, focusing on the transaction side. While much blockchain research has focused on how the technology may affect strategic choices, this study has shed light on its potential from the perspective of financial reporting. Second, by highlighting the importance of the demand for the prompt identification of losses, this work adds to the body of knowledge on the factors that influence transaction frauds involving paper money. Additionally, by establishing the link between transparency and virtual transactions, the author backs up the asymmetric responses of investors to different investment possibilities. It looks at the evolution of financial technology (Fintech) and shows how it can be used to take the advantage of unique opportunities.

The study is different and novel from the previously published literature on this topic mainly because of its comprehensiveness, as it revolves around all industrial and commercial areas. The three main lines of research have been outlined, namely, classifying the many blockchain-based innovations that will alter the financial landscape in many industries; identifying whether these industries are a good fit for blockchain’s wealth creation potential; and directing researchers by outlining prospective study pathways.

This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.

The authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.

Fifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.

The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.

Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

The purpose here is to show how the “shadow” economy has grown in scale and impetus in recent years, though even before modern times it has been present (e.g. the City of London, Shaxson, 2011) since at least the middle ages. The reasons for this have become complicated, but we can identify some “deep structures” that are common. Firstly, “globalisation” made it easier for multinationals to escape national regulatory regimes. Secondly, one of the ways neoliberal trading regulations allowed such actors to augment their assets was by means of what they initially called “transfer-pricing” but which now is officially known as “profit shifting” through tax havens. Thirdly, the growth in international trade in legal and illegal ways caused money laundering – even by otherwise respectable banks – to grow across borders. Conversely, from the supply-side, tax haven status was increasingly accessed by jurisdictions that sought to achieve economic growth by supplying tax haven services, both Delaware and Ireland as exemplars of a “developmental” fiscal policy.

This paper adopts a “pattern recognition” design, an approach that is abductive, meaning interpretive, as shown in the observation that explanation can be valid or reliable without direct observation. This is shown in the indirect observation that “rain fell because the terrace has puddles” or “ancient glaciers once carved this valley”.

Reviewing the European Union’s (EU) list of non-co-operating jurisdictions in support of the OECD’s review of base erosion and profit-shifting activity, Collin concluded the EU’s listing “moved the needle” somewhat but was only a modest success. This is because of its reluctance to sanction its own members or large economies like the USA. Data on foreign direct investment and offshore banking assets suggest listed jurisdictions did not suffer notably from being named and shamed. In all cases studied, this contribution found legally damaging, fraudulent, conflict of interest and corrupt practice activities everywhere.

The originality is found in three spheres. Firstly, the pattern recognition method was vindicated in yielding hard to research results. Secondly, the “assemblage-thirdspace” theory was found advantageous in demonstrating the uneven geography of tax haven clusters and their common history in turbocharging economic development. Finally, the empirics showed the ruses executed by cluster members in tax havens to circumvent the law from global management consultancies to micro-firms consisting of tax lawyers and other experts interacting in knowledge supply chains of dubious morality.

Environmental impact and changes are becoming essential in textile and yarn industries, where reliable measurement of parameters related to processing harmful substances needs to be examined. Such findings can be cumulated using smart assessment like life cycle analysis. The ecological impact category, supply chain, and climate-changing factors were considered for the necessary assessment.

This paper applies the Life Cycle Assessment technique in the textile and yarn industry to estimate critical environmental potentials. The critical input for the fabric and yarn industry was put in the GaBi software model to estimate various environmental potentials.

Global warming potential, electricity, and raw cotton consumption in the fabric and yarn industry were critical concerns where attention should be focused on minimizing environmental potentials from cradle to gate assessment.

This qualitative study is made via the industry case-wise inputs and outputs, which can vary with demographic conditions. Some machine and human constraints have not been implemented in modelling life cycle model for smart simulation. Smart simulation helps in linking different parameters and simulates their combined effects on the product life cycle.

This modelling approach will help access pollution constituents in different supply chain production processes and optimize them simultaneously.

The raw data used in this analysis are collected from an Indian small scale textile industry. In the textile fabrication industry, earlier assessments were carried out in cotton generation, impact of PET, cradle to grave assessment of textile products and garment processing only. In this research the smart model is drawn to consider each input parameter of yarn and textile fabric to determine the criticality of each input in this assessment. This article mainly talks about life cycle and circular supply assessment applied to first time for both cotton to yarn processing and yarn to fabric industry for necessary estimation of environment potentials.

This study deals with three major topics: (1) the developed generations of 3D concrete printers, (2) the mix design approach for cement-based materials and (3) laboratory testing.

The big question is how to approach and follow the trend of 3D concrete printing technology with limited conditions such as printers, technology issues and budget. Therefore, this research focused on dealing with prominent issues, including printing equipment, mixed proportion design approaches and laboratory testing methods will be presented and analyzed.

The details of three printing equipment, including a printhead, a small-scale 3D printer, a 3D concrete printer and the printing process related to Simplify and Mach3 software, will be revealed. Secondly, the classification and efficient process will be given according to the mixture proportion design method proposed. Thirdly, laboratory testing will be conducted, including extrudability, buildability and printability. Finally, some highlight conclusions are given based on the appearance and quality of the samples printed.

Research has been carried out with cement-based materials and 3D concrete printer which adopted the screw extruders.

Mix design proportion method via coefficient and slump value proposed by the authors is a relatively effective and convenient method; the rheological properties, printing process and geometry of a sample are the most significant factors that decide the success of the printing work.

Additive manufacturing, widely known as 3D printing, has recently drawn the attention of researchers worldwide for a few decades. Thanks to its capability to transform a drawing into an object, the idea of 3D printing has also attracted the attention of engineers, architects and investors.

(1) Mix design proportion via coefficient and slump value proposed by the authors is a relatively effective and convenient method that can be implemented simply at the laboratory or the site. (2) The ranges of coefficients by weight of the water, sand and PP fibers to binder are (0.27–0.3), (0.6–1.0) and around 0.3, respectively. The maximum sand size was smaller than 2.5 mm, and the small amount of PP fibers enhanced the quality and significantly reduced the printed samples' shrinkage. (3) The printability is affected by mix proportion and the relationship between nozzle printing speed parameter and extrusion speed of motor turning. (4) The chosen layer height recommended smaller than 0.83 times nozzle diameter is reasonable and improves adhesions and buildability. (5) The printing open time of the concrete mixture of (12–15) minutes is a barrel to promote 3D concrete printing technology and needs improvement.

Assess the realistic impacts of implementing an Radio Frequency Identification (RFID)/Internet of Things (IoT) uniforms’ distribution system for managing medical personnel’s scrubs in operating rooms. The authors use a hybrid simulation framework to address the following objectives and challenges: a) reduce and control operating rooms’ level of inventory; b) stabilize scrubs’ demand and c) improve infection control and prevention of cross-contamination (through scrubs over manipulation and hoarding).

The authors adopt a Design Science approach. This methodological approach is used to design, develop, create and evaluate information technology “artifacts” (e.g. constructs, models, methods and instantiations) intended to solve organizational problems and make research contributions (Peffers et al., 2007). More specifically, the authors follow the Design Science Research Methodology process model which includes six steps: problem identification and motivation, definition of the objectives for a solution, design and development, demonstration, evaluation, and communication.

To assess the realistic impacts of implementing an RFID-IoT uniforms’ distribution system for managing medical personnel’s scrubs in operating rooms, the authors adopted a design science approach and initiated the research by documenting the business case and reviewed the existing literature to build a comparative analysis of existing uniforms’ distribution systems. The authors used a hybrid simulation model to assess the impact of three business cases: present mode of operation, implementing smart shelves or the smart distributors. The authors show that smart dispensers allow a greater control on scrubs’ utilization while eliminating the cross-contamination of the medical personnel.

Through this research study, the authors provide hospitals’ managers a scientific support for uniforms’ (scrubs) distribution process improvement. The authors use a hybrid simulation model to compare innovative solutions for uniforms’ distribution systems in the form of “smart cabinets” supported by Radio Frequency Identification (RFID)/Internet of Things (IoT) technologies and choose the most appropriate design for the hospital to meet two main challenges: a) inefficiency of uniform replenishment-distribution system and b) noncompliancy with infection control regulations caused by the distribution system.

From a methodological perspective, this paper addresses concerns from researchers calling quantitative research methods and using case-based research strategy to address IoT issues and assess the system in practice. From a broader point of view, this work confirms the predominant interest of RFID-IoT research work in the arena of supply chain management and logistics as the technology is used for tracking purpose and for monitoring applications. It is also one response to the research community suggesting that “hospitals should evaluate the medical effectiveness of the new technologies as well as the cost before adoption”.

This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.

The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.

The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.

This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.

The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.

This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.