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Hybrid nanofluids are more effective in the enhancement of heat transfer than mono nanofluids. The mono nanofluid’s thermophysical properties are limited, so it is not enough to succeed in the required thermal performance. The Darcy–Forchheimer hybrid nanofluid flow based on Ag and TiO2 has been used for the applications of drug delivery. In photoelectrochemical (PEC) biosensing applications, the detection of targets has been greatly enhanced by the use of various TiO2 nanostructures. Biosensors, drug delivery systems and medical devices can benefit greatly from the combination of Ag and TiO2.

The Ag and TiO2 hybrid nanofluid flow in an inclined squeezing channel is considered for the applications of drug delivery. The channel walls are permeable and allow fluid in the form of suction and injection, while the flow medium inside the channel is also nonlinearly porous. A set of nonlinear differential equations is created from the main governing equations. The model problem is solved by using the artificial neural network (ANN), and the results are plotted and discussed. Recent and past results have been observed to have a strong correlation.

It can be concluded that the contracted and expanding parameter nature is the main factor in controlling hybrid nanofluid flow in the inclined squeezing flow. The values of the other parameters vary the profile’s growth. The central zone has the lowest absolute value of normal pressure drop for the pair of cases with positive or negative Reynolds. The lower heated wall becomes more efficient when the increase is used with a 5% volume fraction. The lower wall has an increasing percentage of 6.9% and 9.75% when using nanofluid and hybrid nanofluid, respectively.

The authors believe that no one has ever investigated the Darci–Forchheimer flow in a squeezing inclined channel for medical applications. The physical properties of the Ag and TiO2 hybrid nanofluid make it suitable for use as a medication in the biomedical field. The ANN is also a novel approach to solving the current problem. This research is focused on stabilizing hybrid nanofluid flow in the squeezing and porous channels by optimizing normal pressure under the influence of embedded parameters. This main part of the research is not usually mentioned in the existing literature.

Hybrid nanofluids can effectively utilize the antimicrobial properties of TiO2 and Ag nanomaterials for drug delivery applications due to their unique properties. Ag and TiO2 nanomaterials have the ability to control temperature distribution during the flow in an inclined channel, which is crucial for uniform drug delivery. Controlling the release rate of drugs and maintaining the flow stability is largely dependent upon the increase in temperature. The Ag and TiO2 nanoparticles are effective in localized hyperthermia treatments, and this procedure necessitates a temperature higher than the body’s temperature. Therefore, increasing the temperature profile is essential for drug delivery.

Hybrid nanofluids can effectively utilize the antimicrobial properties of TiO2 and Ag nanomaterials for drug delivery applications due to their unique properties. Ag and TiO2 nanomaterials have the ability to control temperature distribution during the flow in an inclined channel, which is crucial for uniform drug delivery. Controlling the release rate of drugs and maintaining the flow stability is largely dependent upon the increase in temperature. The Ag and TiO2 nanoparticles are effective in localized hyperthermia treatments, and this procedure necessitates a temperature higher than the body’s temperature. Therefore, increasing the temperature profile is essential for drug delivery.

The authors believe that no one has ever investigated the Darci–Forchheimer flow in a squeezing channel for medical applications. Moreover, the walls of the channel and the flow medium are both porous. The physical properties of the Ag and TiO2 hybrid nanofluid make it suitable for use as a medication in the biomedical field. The idea of a hybrid nanofluid flow in a squeeze channel using blood-based Ag and TiO2 is also new and important for drug delivery applications. The ANN is also a novel approach to solving the current problem.

This paper explores information flows in the news media amid ideological polarization, focusing on challenges and opportunities. The case study of Donald Trump’s sneaker line unveiling examines how news agencies navigate objectivity in reporting politically sensitive topics online. It also explores the balance news supply chains must strike between expediency, objectivity and differentiation for diverse audiences.

The study conducts qualitative and quantitative content analysis on mainstream media coverage of Donald Trump’s sneaker unveiling. Meticulous coding and inductive approaches systematically review news stories to uncover trends and variations. Incorporating media bias ratings provides context on potential framing biases. This rigorous methodology aims to locate emergent themes in how news outlets interpret and report on politically charged events, offering reliable insights into the dynamics of reporting on contentious narratives.

The analysis reveals polarized reactions to Trump’s sneaker unveiling, reflecting societal divisions. Aesthetics underscore manipulative political messaging and ethical dilemmas. Varying press reception mirrors broader tensions across online news media. Coverage suggests a link between media bias and sentiment toward Trump. Theoretical insights explore dynamic capabilities and social identity theory. The study offers practical implications for navigating ideological framing and audience engagement, benefiting news media supply chain professionals.

This paper provides novel insights into online news supply chains, revealing complexities in reporting politically charged events. It contributes theoretical perspectives on dynamic capabilities and social identity theory and offers practical implications for managing ideological framing in online news media, adding significantly to existing knowledge.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2024-0241

The study aims to outline and hierarchically rank the key enablers that support the digital nomad lifestyle, identifying their interrelationships and contextual importance within the ecosystem.

The study utilizes a multi-method approach encompassing modified total interpretive structural modeling (m-TISM) and matrice d’impacts croisés multiplication appliquée à un classement (MICMAC) analysis, complemented by a one-tailed t-test to validate the model.

The research identified nine crucial enablers that facilitate the digital nomad lifestyle. The study effectively maps out their hierarchical relationships and the dynamics of their interactions.

While the study offers significant insights, it relies heavily on expert opinions, which may introduce subjective bias. Additionally, the dynamic nature of digital nomadism might limit the long-term applicability of the findings.

The findings have substantial implications for policymakers and corporate leaders. By understanding the key enablers and their interactions, stakeholders can develop targeted strategies that enhance support for digital nomads, potentially increasing organizational flexibility and global reach.

This study contributes original insights by applying an advanced m-TISM approach to the digital nomad sector, a topic of growing relevance in post-pandemic work arrangements. It provides a comprehensive framework that integrates various theoretical and practical perspectives, which were fragmented previously.

The purpose of studying the impact of crude oil and natural gas prices on the Vietnamese stock market is to understand the relationship between energy prices and the overall performance of the financial markets. As Vietnam is an energy-dependent country, fluctuations in crude oil and natural gas prices can significantly affect various industries, including manufacturing, inflation, transportation, energy production and economic growth. These sectors are often sensitive to changes in energy costs, which can lead to shifts in corporate profitability and investor sentiment. By analyzing how crude oil and natural gas prices influence the Vietnamese stock market, policymakers and investors can provide deeper insights into the economic risks and opportunities related to energy price volatility. This paper can also provide valuable information for decision-making in sectors such as economic forecasting, risk management and investment strategies.

Using monthly data from January 2006 to March 2024, data were collected from the Vietnamese stock market and the OPEC organization for oil prices, while data on natural gas were obtained from the EIA. The data were analyzed using vector error correction (VEC) model, impulse response function, variance decomposition test and asymmetric reactions method; the study tries to ascertain the short-term and long-term dynamic relationships between the shocks of the crude oil price and natural gas prices and their effects on the movement of the stock price. In addition, the GARCH model is applied to measure the volatility of crude oil and natural gas prices.

Crude oil price shocks have a statistically significant impact on most Vietnamese real stock market indices, except for the utility and consumer indices and some energy companies. Conversely, natural gas price shocks do not significantly affect on Vietnamese stock market indices, except for the energy index and some energy companies. Some “important” of both crude oil price and natural gas price shocks tend to depress the stock returns of energy companies. An increase in both crude oil and natural gas volatility can lead to heightened speculation in certain indices, particularly the energy and industrial indices, as well as in some energy companies. This heightened speculation often results in elevated of their stock returns.

This study provides valuable insights into the field of study examining how fluctuations in the prices of oil and gas, particularly during major crisis periods such as global financial crisis, COVID-19 pandemic and the Russo-Ukrainian War, affect financial markets.

The objective of this article is to analyze the mediating role of innovation capability—both radical and incremental—between technological turbulence and digital innovation ecosystem performance, considering the impact of cross-organizational knowledge sabotage. Despite the enthusiasm surrounding digitization, the high failure rate (80%) of digital transformation projects has received limited attention. This alarming statistic indicates a potential rise in opportunistic behaviors within organizations. We hypothesize that employees seeking to reduce the risk of being displaced by digital technologies, may not only hide knowledge, as previously observed, but also engage in knowledge sabotage by disseminating inaccurate information during the co-creation of digital innovations within the digital innovation ecosystem.

The study employed structural equation modeling to examine moderated mediation using survey data collected from 148 firms, mainly from sectors of high to medium levels of digital intensity.

The most significant finding indicates that cross-organizational knowledge sabotage considerably reduces the only mediating effect, namely that of incremental innovation capability.

Our study presents a novel perspective by investigating the phenomenon of cross-organizational knowledge sabotage. Unlike prior research, which primarily identified the existence of knowledge hiding, our findings suggest that employees are not only willing to withhold information but also to disseminate inaccurate information to external partners. Consequently, our research extends the boundaries of the existing knowledge field by demonstrating that cross-organizational knowledge sabotage has repercussions that extend beyond intra-organizational impacts, as previously recognized. It also adversely affects the outcomes of collaborative work within the digital innovation ecosystem.

This paper presents a conceptual framework based on an extensive literature review. The aim of this study is to deepen understanding of the relationship between carbon performance and the financial market by applying qualitative research approaches.

The investigation has identified 372 articles sourced from Scopus databases, subjecting the bibliographic data to a comprehensive qualitative–quantitative analysis. The research uses established protocols for a structured literature review, adhering to PRISMA guidelines, machine learning-based structural topic modelling using Python and bibliometric citation analysis.

The results identified the leading academic authors, institutions and countries concerning carbon performance and financial markets literature. Quantitative studies dominate this research theme. The study has identified six knowledge clusters using topic modelling related to environmental reporting; price drivers of carbon markets; environmental policy and capital markets; financial development and carbon emissions; carbon risk and financial markets; and environmental performance and firm value. The results of the study also present the opportunities associated with carbon performance and the financial market and propose future research agendas on research through theory, characteristics, context and methodology.

The results of the study offer insights to practitioners, researchers and academicians regarding scientific development, intricate relationships and the complexities involved in the intersection of carbon performance and financial markets. For policymakers, a better understanding of carbon performance and financial markets will contribute to designing policies to set up priorities for countering carbon emissions.

The study highlights the critical areas that require attention to limit greenhouse gas emissions and promote decarbonisation effectively. Policymakers can leverage these insights to develop targeted and evidence-based policies that facilitate the transition to a more sustainable and low-carbon economy.

The study initially attempts to discuss the research stream on carbon performance and financial markets literature from a systematic literature review.

Entrepreneurial activities significantly contribute to economic growth and job creation, making entrepreneurship an attractive career path. While students’ entrepreneurial intentions in traditional fields like economics, business and engineering have been widely studied, less attention has been given to nontraditional fields, especially in emerging economies. This study aims to address this gap by exploring the entrepreneurial intentions of health sciences students in Colombian universities, a context marked by unique socioeconomic and cultural factors.

The study surveyed 202 students across three colleges. Confirmatory factor analysis and structural equation modeling were used to validate the theorized relationships and analyze the data.

Preliminary findings indicate a positive correlation between personal attitudes and educational support with entrepreneurial intentions among health science students. Contrary to expectations, the influence of family roles and broader sociocultural contexts appeared less significant, suggesting a distinct pattern within this field.

This paper presents a detailed study of the factors influencing the entrepreneurial intention of health sciences students in higher education. It provides theoretical and practical insights, contributing to the existing literature on entrepreneurial intention. The findings can be used by institutions to develop targeted training programs tailored to students’ specific needs.

The purpose of this paper is to measure price risk transfer from futures prices to spot prices in the markets of energy commodities.

To this end, it estimates CoVaR functions for five futures-spot prices pairs of energy commodities. To account for the effects of the Covid-19 pandemic as well as for the effects of the Russo−Ukrainian conflict, the total sample has been split into three sub-samples. The first one contains observations from 01/01/2010–3/11/2020, which marks the official declaration of the coronavirus as a global pandemic. The second sub-sample uses observations from 3/12/2020–2/24/2022, which marks the beginning of the Russo−Ukrainian conflict, and the third one includes observations from 2/25/2022 up to 8/31/2023.

Results indicate that the effect of the coronavirus pandemic was to increase the risk of price transfer from futures markets to spot markets, in all of the energy commodities examined. On the other hand, the effect of the escalation of the Russo−Ukrainian conflict was to significantly reduce the price risk transfer from the futures markets to the spot markets, in all five energy commodities.

To the best of the authors’ knowledge, this is the first study to use CoVaR functions to estimate risk transfer among the energy commodities. In addition, it separates and estimates the effects of the Covid-19 pandemic as well as the effects of the Russo−Ukrainian conflict.

This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.

The study employs the TVP-VAR extension of the spillover index framework to scrutinize the information spillovers among the energy, agriculture, metal, and carbon markets. Subsequently, the study explores practical applications of these findings, emphasizing how investors can harness insights from information spillovers to refine their investment strategies.

First, the CEA provide ample opportunities for portfolio diversification between the energy, agriculture, and metal markets, a desirable feature that the EUA does not possess. Second, a portfolio comprising exclusively energy and carbon assets often exhibits the highest Sharpe ratio. Nevertheless, the inclusion of agricultural and metal commodities in a carbon-oriented portfolio may potentially compromise its performance. Finally, our results underscore the pronounced advantage of minimum spillover portfolios; particularly those that designed minimize net pairwise volatility spillover, in the context of China's national carbon market.

This study addresses the previously unexplored intersection of information spillovers and portfolio diversification in major commodity markets, with an emphasis on the role of CEA.