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Article
Publication date: 28 November 2023

Marvelous Kadzima, Michael Machokoto and Edward Chamisa

This study empirically examines the nonlinear effects of mimicking peer firms' cash holdings on shareholder value, with consideration of macroeconomic conditions.

Abstract

Purpose

This study empirically examines the nonlinear effects of mimicking peer firms' cash holdings on shareholder value, with consideration of macroeconomic conditions.

Design/methodology/approach

An instrumental variable approach for nonlinear models is estimated for a large sample of US firms over the period 1991–2019. This approach addresses the reflection problem in examining peer effects, whereby it is impossible to separate the individual's effects on the group, or vice versa, if both are simultaneously determined.

Findings

The authors find an inverted U-shaped association between shareholder value and mimicking intensity of peer firms' cash holdings. This result suggests that mimicking peer firms' cash holdings is subject to diminishing returns. It is more beneficial at lower levels of mimicking intensity but less so or suboptimal at higher levels. Further evidence indicates that this inverted U-shaped shareholder value-mimicking intensity nexus is asymmetric. Specifically, it is salient for decreases relative to increases in cash holdings and, more importantly, in good relative to bad macroeconomic states. The findings are robust to several concerns and have important implications for liquidity management policies.

Originality/value

The authors provide new empirical evidence of the nonlinear effects of mimicking peer firms' cash holdings on shareholder value, which varies with macroeconomic conditions.

Details

International Journal of Managerial Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1743-9132

Keywords

Article
Publication date: 4 July 2023

Neeraj Jain and Smita Kashiramka

This study aims to investigate the effects of peers on corporate payout policies in one of the largest emerging markets – India. It also examines the motives for mimicking payout…

Abstract

Purpose

This study aims to investigate the effects of peers on corporate payout policies in one of the largest emerging markets – India. It also examines the motives for mimicking payout decisions.

Design/methodology/approach

The sample is composed of 3,024 non-financial and non-government firms listed on the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) for the period 1995 to 2020. To encounter the endogeneity problem, the instrumental variable technique based on peer firms' idiosyncratic risk is used to estimate the effects of peers on firms' payout policy. To define peer reference groups, the authors use the basic industry classification of the firms.

Findings

The results indicate a significant positive impact of peers on firms' dividend policies in India. A firm with all dividend-paying peers is more likely to declare dividends than the one with no dividend-paying peers. Further, peer effects are found to be more pronounced amongst larger and older firms, thus supporting the rivalry theory of mimicking.

Originality/value

To the best of the authors' knowledge, the present study is the first of its kind that attempts to understand peer effects on payout decisions in an emerging market India, that offers a unique institutional setting. Moreover, the authors extend the existing literature by investigating the peer effects on a firm's payout policies considering various firm-level characteristics, such as growth opportunity, cash holding, financial constraint and profitability, which previous studies have not taken into consideration. These results provide additional insights into the heterogeneity and motives behind peer effects.

Details

International Journal of Managerial Finance, vol. 20 no. 2
Type: Research Article
ISSN: 1743-9132

Keywords

Article
Publication date: 2 January 2024

Dimitrios Markopoulos, Anastasios Tsolakidis, Ioannis Triantafyllou, Georgios A. Giannakopoulos and Christos Skourlas

This study aims to analyze a conspicuous corpus of literature related to the field of technology-based intensive care research and to develop an architecture model of the future…

Abstract

Purpose

This study aims to analyze a conspicuous corpus of literature related to the field of technology-based intensive care research and to develop an architecture model of the future smart intensive care unit (ICU).

Design/methodology/approach

Papers related to the topics of electronic health record (EHR), big data, data flow and clinical decision support in ICUs were investigated. These concepts have been analyzed in combination with secondary use of data, prediction models, data standardization and interoperability challenges. Based on the findings, an architecture model evaluated using MIMIC III is proposed.

Findings

Research identified issues regarding implementation of systems, data sources, interoperability, management of big data and free text produced in ICUs and lack of accuracy of prediction models. ICU should be treated as part of a greater system, able to intercommunicate with other entities.

Research limitations/implications

The research examines the current needs of ICUs in interoperability and data management. As environment changes dynamically, continuous assessment and evaluation of the model with other ICU databases is required.

Originality/value

The proposed model improves ICUs interoperability in national health system, ICU staff intercommunication, remote access and decision support. Its modular approach ensures that ICUs can have their own particularities and specialisms while ICU functions provide ongoing expertise and training to upgrade its staff.

Details

Global Knowledge, Memory and Communication, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9342

Keywords

Article
Publication date: 2 November 2023

Minyi Zhu, Guobin Gong, Xuehuiru Ding and Stephen Wilkinson

The study aims to investigate the effects of pre-loading histories (pre-shearing and pre-consolidation) on the liquefaction behaviour of saturated loose sand via discrete element…

Abstract

Purpose

The study aims to investigate the effects of pre-loading histories (pre-shearing and pre-consolidation) on the liquefaction behaviour of saturated loose sand via discrete element method (DEM) simulations.

Design/methodology/approach

The pre-shearing history is mimicked under drained conditions (triaxial compression) with different pre-shearing strain levels ranging from 0% to 2%. The pre-consolidation history is mimicked by increasing the isotropic compression to different levels ranging from 100 kPa to 300 kPa. The macroscopic and microscopic behaviours are analysed and compared.

Findings

Temporary liquefaction, or quasi-steady state (QSS), is observed in most samples. A higher pre-shearing or pre-consolidation level can provide higher liquefaction resistance. The ultimate state line is found to be unique and independent of the pre-loading histories in stress space. The Lade instability line prematurely predicts the onset of liquefaction for all samples, both with and without pre-loading histories. The redundancy index is an effective microscopic indicator to monitor liquefaction, and the onset of the liquefaction corresponds to the phase transition state where the value of redundancy index is one, which is true for all cases irrespective of the proportions of sliding contacts.

Originality/value

The liquefaction behaviour of granular materials still remains elusive, especially concerning the effects of pre-loading histories on soils. Furthermore, the investigation of the effects of pre-consolidation histories on undrained behaviour and its comparison to pre-sheared samples is rarely reported in the DEM literature.

Details

Engineering Computations, vol. 40 no. 9/10
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 16 June 2023

Mohammad Kamal Abuamsha and Lana Majdi Hattab

The present research aims at identifying the latent factors that are driving the rise of the shadow economy in Palestine, assesses its magnitude from 1998 to 2021 and investigates…

Abstract

Purpose

The present research aims at identifying the latent factors that are driving the rise of the shadow economy in Palestine, assesses its magnitude from 1998 to 2021 and investigates the influence that its size has on the financial sustainability of Palestine's public budget.

Design/methodology/approach

The researchers employed the multi-indicator multi-causes (MIMIC) model to estimate the size of the shadow economy and investigate its effect on the financial sustainability of the public budget. Economic factors such as direct taxes, indirect taxes, government welfare, government spending and unemployment were considered causal variables, while indicators of financial sustainability included budget deficit, public debt and gross domestic product (GDP). The shadow economy served as an intermediary variable.

Findings

Based on the findings, the researchers recommend regulating and formalizing legitimate activities within the shadow economy. Additionally, they suggest promoting investment projects to reduce unemployment rates, lowering taxes on essential goods and consumer items and providing support to local producers in Palestine. These measures aim at addressing the challenges posed by the shadow economy and fostering economic stability.

Originality/value

The study reveals that the average size of the shadow economy in Palestine between 1998 and 2021 was 43.80%, fluctuating within the range of 39.92%–46.30%. It further establishes that an increase in direct and indirect taxes as well as unemployment contributes to the expansion of the shadow economy. Conversely, government welfare and spending exert a diminishing effect. Moreover, the study finds that the rise of the shadow economy correlates with an increase in public debt, budget deficit and GDP, indicating a negative impact on the financial sustainability of the public budget.

Details

Journal of Economic Studies, vol. 51 no. 2
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 15 April 2024

Majid Monajjemi and Fatemeh Mollaamin

Recently, powerful instruments for biomedical engineering research studies, including disease modeling, drug designing and nano-drug delivering, have been extremely investigated…

Abstract

Purpose

Recently, powerful instruments for biomedical engineering research studies, including disease modeling, drug designing and nano-drug delivering, have been extremely investigated by researchers. Particularly, investigation in various microfluidics techniques and novel biomedical approaches for microfluidic-based substrate have progressed in recent years, and therefore, various cell culture platforms have been manufactured for these types of approaches. These microinstruments, known as tissue chip platforms, mimic in vivo living tissue and exhibit more physiologically similar vitro models of human tissues. Using lab-on-a-chip technologies in vitro cell culturing quickly caused in optimized systems of tissues compared to static culture. These chipsets prepare cell culture media to mimic physiological reactions and behaviors.

Design/methodology/approach

The authors used the application of lab chip instruments as a versatile tool for point of health-care (PHC) applications, and the authors applied a current progress in various platforms toward biochip DNA sensors as an alternative to the general bio electrochemical sensors. Basically, optical sensing is related to the intercalation between glass surfaces containing biomolecules with fluorescence and, subsequently, its reflected light that arises from the characteristics of the chemical agents. Recently, various techniques using optical fiber have progressed significantly, and researchers apply highlighted remarks and future perspectives of these kinds of platforms for PHC applications.

Findings

The authors assembled several microfluidic chips through cell culture and immune-fluorescent, as well as using microscopy measurement and image analysis for RNA sequencing. By this work, several chip assemblies were fabricated, and the application of the fluidic routing mechanism enables us to provide chip-to-chip communication with a variety of tissue-on-a-chip. By lab-on-a-chip techniques, the authors exhibited that coating the cell membrane via poly-dopamine and collagen was the best cell membrane coating due to the monolayer growth and differentiation of the cell types during the differentiation period. The authors found the artificial membrane, through coating with Collagen-A, has improved the growth of mouse podocytes cells-5 compared with the fibronectin-coated membrane.

Originality/value

The authors could distinguish the differences across the patient cohort when they used a collagen-coated microfluidic chip. For instance, von Willebrand factor, a blood glycoprotein that promotes hemostasis, can be identified and measured through these type-coated microfluidic chips.

Details

Sensor Review, vol. 44 no. 3
Type: Research Article
ISSN: 0260-2288

Keywords

Open Access
Article
Publication date: 25 April 2024

Ilse Valenzuela Matus, Jorge Lino Alves, Joaquim Góis, Paulo Vaz-Pires and Augusto Barata da Rocha

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process…

148

Abstract

Purpose

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

Design/methodology/approach

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

Findings

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

Originality/value

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

Details

Rapid Prototyping Journal, vol. 30 no. 11
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 19 March 2024

Diana Irinel Baila, Filippo Sanfilippo, Tom Savu, Filip Górski, Ionut Cristian Radu, Catalin Zaharia, Constantina Anca Parau, Martin Zelenay and Pacurar Razvan

The development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM…

Abstract

Purpose

The development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM) processes, have gained significant attention in recent years. Their accuracy, multi-material capability and application in novel fields, such as implantology, biomedical, aviation and energy industries, underscore the growing importance of these materials. The purpose of this study is oriented toward the application of new advanced materials in stent manufacturing realized by 3D printing technologies.

Design/methodology/approach

The methodology for designing personalized medical devices, implies computed tomography (CT) or magnetic resonance (MR) techniques. By realizing segmentation, reverse engineering and deriving a 3D model of a blood vessel, a subsequent stent design is achieved. The tessellation process and 3D printing methods can then be used to produce these parts. In this context, the SLA technology, in close correlation with the new types of developed resins, has brought significant evolution, as demonstrated through the analyses that are realized in the research presented in this study. This study undertakes a comprehensive approach, establishing experimentally the characteristics of two new types of photopolymerizable resins (both undoped and doped with micro-ceramic powders), remarking their great accuracy for 3D modeling in die-casting techniques, especially in the production process of customized stents.

Findings

A series of analyses were conducted, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, mapping and roughness tests. Additionally, the structural integrity and molecular bonding of these resins were assessed by Fourier-transform infrared spectroscopy–attenuated total reflectance analysis. The research also explored the possibilities of using metallic alloys for producing the stents, comparing the direct manufacturing methods of stents’ struts by SLM technology using Ti6Al4V with stent models made from photopolymerizable resins using SLA. Furthermore, computer-aided engineering (CAE) simulations for two different stent struts were carried out, providing insights into the potential of using these materials and methods for realizing the production of stents.

Originality/value

This study covers advancements in materials and additive manufacturing methods but also approaches the use of CAE analysis, introducing in this way novel elements to the domain of customized stent manufacturing. The emerging applications of these resins, along with metallic alloys and 3D printing technologies, have brought significant contributions to the biomedical domain, as emphasized in this study. This study concludes by highlighting the current challenges and future research directions in the use of photopolymerizable resins and biocompatible metallic alloys, while also emphasizing the integration of artificial intelligence in the design process of customized stents by taking into consideration the 3D printing technologies that are used for producing these stents.

Article
Publication date: 29 December 2023

Haining Sun and Jianhu Cai

This paper aims to study the preferences of the supply chain (SC) members on various power structures under demand information asymmetry considering competing retailers.

Abstract

Purpose

This paper aims to study the preferences of the supply chain (SC) members on various power structures under demand information asymmetry considering competing retailers.

Design/methodology/approach

A two-level SC with one manufacturer and two retailers is designed. The retailers are in Bertrand competition. The manufacturer who holds the confidential demand information chooses the appropriate information sharing (IS) format. Three IS formats are provided, i.e. no IS (the manufacturer never shares with the retailers), partial IS (the manufacturer shares with one retailer), full IS (the manufacturer shares with all retailers). In addition, the authors model two power structures based on the decision sequences in the SC, i.e. retailers or manufacturer-dominant SC. The authors characterize the equilibrium solutions and payoffs and then investigate the members’ preferences for IS formats.

Findings

It is shown that in retailers (manufacturer)-dominant SC, the retailers prefer full (no) IS, but the manufacturer prefers no (full) IS. Moreover, the authors analyze the members’ preferences on power structures under demand information asymmetry, which has a relationship with the degrees of demand uncertainty and competition intensity.

Originality/value

The analysis regarding the preferences of the SC members on power structure under demand information asymmetry provides valuable managerial insights to enhance cooperation and achieve a win-win result.

Details

Journal of Business & Industrial Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 29 November 2023

Tarun Jaiswal, Manju Pandey and Priyanka Tripathi

The purpose of this study is to investigate and demonstrate the advancements achieved in the field of chest X-ray image captioning through the utilization of dynamic convolutional…

Abstract

Purpose

The purpose of this study is to investigate and demonstrate the advancements achieved in the field of chest X-ray image captioning through the utilization of dynamic convolutional encoder–decoder networks (DyCNN). Typical convolutional neural networks (CNNs) are unable to capture both local and global contextual information effectively and apply a uniform operation to all pixels in an image. To address this, we propose an innovative approach that integrates a dynamic convolution operation at the encoder stage, improving image encoding quality and disease detection. In addition, a decoder based on the gated recurrent unit (GRU) is used for language modeling, and an attention network is incorporated to enhance consistency. This novel combination allows for improved feature extraction, mimicking the expertise of radiologists by selectively focusing on important areas and producing coherent captions with valuable clinical information.

Design/methodology/approach

In this study, we have presented a new report generation approach that utilizes dynamic convolution applied Resnet-101 (DyCNN) as an encoder (Verelst and Tuytelaars, 2019) and GRU as a decoder (Dey and Salemt, 2017; Pan et al., 2020), along with an attention network (see Figure 1). This integration innovatively extends the capabilities of image encoding and sequential caption generation, representing a shift from conventional CNN architectures. With its ability to dynamically adapt receptive fields, the DyCNN excels at capturing features of varying scales within the CXR images. This dynamic adaptability significantly enhances the granularity of feature extraction, enabling precise representation of localized abnormalities and structural intricacies. By incorporating this flexibility into the encoding process, our model can distil meaningful and contextually rich features from the radiographic data. While the attention mechanism enables the model to selectively focus on different regions of the image during caption generation. The attention mechanism enhances the report generation process by allowing the model to assign different importance weights to different regions of the image, mimicking human perception. In parallel, the GRU-based decoder adds a critical dimension to the process by ensuring a smooth, sequential generation of captions.

Findings

The findings of this study highlight the significant advancements achieved in chest X-ray image captioning through the utilization of dynamic convolutional encoder–decoder networks (DyCNN). Experiments conducted using the IU-Chest X-ray datasets showed that the proposed model outperformed other state-of-the-art approaches. The model achieved notable scores, including a BLEU_1 score of 0.591, a BLEU_2 score of 0.347, a BLEU_3 score of 0.277 and a BLEU_4 score of 0.155. These results highlight the efficiency and efficacy of the model in producing precise radiology reports, enhancing image interpretation and clinical decision-making.

Originality/value

This work is the first of its kind, which employs DyCNN as an encoder to extract features from CXR images. In addition, GRU as the decoder for language modeling was utilized and the attention mechanisms into the model architecture were incorporated.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

Keywords

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