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The insurgence of the COVID-19 pandemic insinuated that family-owned small hotels (F-OSH) should adopt AI capabilities and innovation activities and digitize their operations to survive. This study examines the potential of AI capabilities to digitally transform F-OSHs by leveraging innovation ambidexterity, preparing them for future disasters proactively. Additionally, it sheds light on how the impact of AI capabilities on innovation ambidexterity varies based on strategic fit. In addition, this research explores the influence of digital entrepreneurial intention on fostering innovation ambidexterity, essential for digital transformation in F-OSHs.

The study collected primary data from 318 descendant entrepreneurs designated as chairpersons or managing directors in F-OSH and analyzed the data using the partial least structural equation modeling technique.

This study found a positive association of AI capabilities, and digital entrepreneurial intention with the digital transformation of F-OSHs, while strategic fit does not have an association with innovation ambidexterity. Innovation ambidexterity mediates the relationship between AI capabilities and digital transformation in F-OSHs. Moreover, a strong strategic fit increases the effect of AI capabilities on innovation ambidexterity. Furthermore, a high intention for digital entrepreneurship reduces the impact of innovation ambidexterity on the digital transformation of F-OSHs.

The combination of AI capabilities and innovation ambidexterity has transformed F-OSHs' digital transformation. This proactive approach to dealing with economic recessions such as COVID-19 is also influenced by digital entrepreneurial intention and strategic fit.

Anchored on the dynamic capability theory, this study provides valuable insights and novel empirical evidence by investigating the mediating mechanism of innovation ambidexterity and boundary condition of strategic fit and digital entrepreneurial intention between AI capabilities and digital transformation in F-OSHs.

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.

Through the theoretical lens of social practice theory, the aim of this research is to investigate how business-to-business (B2B) high-tech startups build their brands in an omni-digital environment, particularly by focusing on the most important digital touchpoints implemented to interact with stakeholders.

A qualitative analysis was performed by conducting 36 semi-structured interviews with key informants operating in B2B high-tech startups, including founders, CEOs, managing directors, marketing managers and other actors from this sector.

The results reveal the enablers, inhibitors and specific objectives of startups in their brand-building processes across digital touchpoints in an omni-digital environment.

This study offers new theoretical insights into new ventures’ brand management strategies through the development of a theoretical framework in which the enablers, inhibitors and specific objectives of the brand-building process of startups are identified. Although the recent literature has addressed the topic of startup brand building, this is the first study, to the authors’ knowledge, focused on the brand-building process of B2B high-tech startups in an omni-digital environment.

This study aims to identify the factors influencing consumer perception and adoption intention toward online pharmacy.

A questionnaire was formulated based on the unified theory of acceptance and use of technology (UTAUT) framework scales available in the existing literature. An aggregate of 451 respondents participated in the survey. To test the formulated hypothesis, confirmatory factor analysis and structure equation modeling are used for analyzing the structural relationships between dependent and independent variables.

This analysis inspects the significant effect of perceived trust, consumer perception and different UTAUT framework constructs on the adoption intention of online pharmacy consumers. The results determine the substantial moderating effect of perceived trust between adoption intention and consumers’ perception of online pharmacies.

This research extended the application of the UTAUT model with the adoption intention of online pharmacy consumers. Only specific constructs have been selected from the UTAUT model in this study.

The study outcomes are useful to pharmacy managers to realize the role of technological platforms in facilitating the online selling of medicines to pharmacy consumers.

The findings are helpful for pharmaceutical companies to improve their existing online buying process for pharmacy consumers seeking purchase of medicines through online pharmacies.

This analysis is unique and contains newness in the form of the moderating role of perceived trust between constructs of UTAUT and customer adoption of online pharmacies.

As one of the most energy-intensive sectors, the manufacturing industry is strongly affected by current economic, ecological and political issues and is increasingly looking to reduce its energy consumption through effective management. One important component of energy management is monitoring, which can be improved by using the Internet of Things (IoT). This study aims to identify the factors behind the adoption of IoT energy monitoring systems in manufacturing industries and IoT’s impact on consumption in this context. Moreover, this study explores what constitutes successful implementation and develops recommendations on how companies can best use the generated energy-saving potential.

For this purpose, an exploratory, inductive research approach is taken in which five semi-structured interviews with IoT energy-monitoring platform providers located in Germany are conducted and additional documents about these platforms are analysed.

Based on these interviews and documents, this study defines the relevant factors involved in the increased adoption of IoT energy monitoring systems as desired cost reduction, regulatory requirements and customer expectations. Once implemented, a company’s energy efficiency potential strongly depends on its individual situation; however, the transparency characteristic of IoT supports managers in deriving effective energy-saving measures. Additionally, the used efficiency potential is influenced by the level of data collection and organisational capabilities.

To the best of the authors’ knowledge, as the first study, this research combines findings from the energy management and IoT research streams and places them into an organisational context. The application of the fit-viability model as an overarching framework enhances the theoretical contributions of this study. Moreover, focusing on Germany and its substantial industrial sector enables the gathering of important insights and the analysis of the specific use case of industrial IoT, which yields new findings for practitioners as well.

This study examines the relationship between school ties among external auditors and audit committee members, and their joint impact on audit fee. We also examine how the monitoring and executive functions within companies moderate this relationship.

This study employs a regression analysis model on a sample of companies listed on the Indonesia Stock Exchange from 2016 to 2019, followed by additional analyses using high-low growth and tech samples, as well as robustness tests involving coarsened exact matching (CEM) and Heckman’s (1979) theory to address potential causality issues.

This study reveals that school ties between external auditors and audit committees positively influence audit fee. The audit committee size weakens this relationship, while the presence of an internal audit enhances it.

This research contributes to the literature related to the relationship between school ties and audit fee in Indonesian public companies, providing insights for stakeholders and informing company policies. It aims to increase awareness of the significance of school ties among Indonesian companies.

This research fills a knowledge gap by examining the link between audit committee-external auditor relationships and audit fees, aiming to generate new insights and empirical evidence to inform future research and regulatory decisions.

Internet of Things (IoT) is a network, which provides the connection with various physical objects such as smart machines, smart home appliance and so on. The physical objects are allocated with a unique internet address, namely, Internet Protocol, which is used to perform the data broadcasting with the external objects using the internet. The sudden increment in the number of attacks generated by intruders, causes security-related problems in IoT devices while performing the communication. The main purpose of this paper is to develop an effective attack detection to enhance the robustness against the attackers in IoT.

In this research, the lasso regression algorithm is proposed along with ensemble classifier for identifying the IoT attacks. The lasso algorithm is used for the process of feature selection that modeled fewer parameters for the sparse models. The type of regression is analyzed for showing higher levels when certain parts of model selection is needed for parameter elimination. The lasso regression obtains the subset for predictors to lower the prediction error with respect to the quantitative response variable. The lasso does not impose a constraint for modeling the parameters caused the coefficients with some variables shrink as zero. The selected features are classified by using an ensemble classifier, that is important for linear and nonlinear types of data in the dataset, and the models are combined for handling these data types.

The lasso regression with ensemble classifier–based attack classification comprises distributed denial-of-service and Mirai botnet attacks which achieved an improved accuracy of 99.981% than the conventional deep neural network (DNN) methods.

Here, an efficient lasso regression algorithm is developed for extracting the features to perform the network anomaly detection using ensemble classifier.

This study aims to construct comprehensive index of Tahfiz empowerment taking into account various factors such as social, intellectual, physical and religious, as well as economical. According to Maqasid Shariah, Malaysia has to establish a Tahfiz Empowerment Index (TEI) for the implementation of National Tahfiz Education Policy (NTEP) to ensure that Tahfiz institutions assist students’ development in a productive and meaningful way consistent with Islamic values and national educational objectives.

This study proposes the TEI using Maqasid Shariah to offer an organized framework for evaluating and improving the quality and social relevance of Tahfiz institutions. The TEI weaves the five fundamental aims of Maqasid Shariah – preserving religion, protecting life, fostering intellect, preserving lineage and ensuring economic sustainability – into measurable indicators. Comprehensive review of the literature supports the TEI and its using experts, and the TEI assigns equal weightage to each dimension and has provisions to address biases.

The TEI consists of five fundamental aspects: preservation of religion, life, intellect, lineage and economic sustainability. The results imply that systematic way of evaluating and enhancing performance of Tahfiz institution is crucial as the study proves the institution’s importance in the development of its students.

The TEI provides a systematic framework to be used in future empirical research that searches for the operation of Tahfiz institutions and their outcome. Moreover, it serves as a theoretical basis for further research on Islamic education and its alignment with Maqasid Shariah. It also propounds a holistic and inclusive approach encompassing improvement in educational possibilities.

The TEI has useful managerial and policy implications for the improvement of Tahfiz institutions. It can be used as a benchmark whenever the policymaker is in doubt about the quality, safety and equitable distribution of resources in education to achieve Malaysia’s NTEP objectives. The TEI also provides practical, tangible performance indicators for evaluation and benchmarking, resource allocation and strategy planning. It integrates Maqasid Shariah principles, focusing on areas like spiritual and intellectual development, economic sustainability and community engagement.

The TEI as part of Sustainable Development Goals 2030 contributes to social benefits: integrating the principles of Islamic education and human dignity and social welfare. It erases the existing gaps by providing the necessary means through such practices as offering vocational training to underprivileged students, contributes to social responsibility by enhancing mental health and encouraging services to the community, and ultimately improves community involvement through volunteerism and collaborations. Also, TEI directs the distribution of funds toward programs that should benefit underprivileged learners, thus maintain sustainable fund allocation as well as promoting social responsibility as per NTEP objectives.

This study presents a novel index grounded on Maqasid Shariah which is useful for assessing and improving the Tahfiz institutions. It gives a definite and systematic method of evaluating these institutions’ degrees of empowerments to meet all the diverse roles they play in the society.

High surface area-to-volume ratios make nanoparticles ideal for cancer heat therapy and targeted medication delivery. Moreover, ternary nanofluids (TNFs) may possess superior thermophysical properties compared to mono- and hybrid nanofluids due to their synergistic effects. In light of this information, the objective of this article is to examine the blood-based TNF flow within convergent/divergent channels under velocity slip and temperature jump.

Leading partial differential equations corresponding to the problem are transformed into a system of nonlinear ordinary differential equations by using similarity variables. The bvp4c code that uses the finite difference method is used to obtain a numerical solution.

The effect of nanoparticles may change depending on the characteristics of flow near the wall. The properties and proportions of the used nanoparticles become important to control the flow. When TNF was used, an increase in the Nusselt number between 4.75% and 6.10% was observed at low Reynolds numbers. At high Reynolds numbers, nanoparticles reduce the Nusselt number and skin friction coefficient values under some special flow conditions. Importantly, the effects of second-order slip on engineering parameters were also investigated. Furthermore, the Nusselt number increases with increasing shape factor.

Obtained results of the study can be beneficial in both nature and engineering, especially blood flow in veins.

The main innovations of this study are the usage of blood-based TNF and the examination of the effect of shape factor in convergent/divergent channels with second-order velocity slip.

This paper aims to explore the numerical simulation of MHD flow of Williamson hybrid nanofluid over a porous stretched sheet. Cattaneo–Christov thermal and specie fluxes were used in the model. Partial differential equations are exploit to model the underlying physics of the situation (PDEs).

Using an acceptable similarity functions, these equations were changed into total differential equations (ODEs). The spectral relaxation method (SRM) was used to solve the linked and nonlinear altered ODEs. The Gauss–Seidel procedure is used to figure out how to use Chebyshev pseudospectral techniques in SRM. This is an iterative process.

Increasing the heat relaxation flow increases temperature distributions; increasing the mass relaxation flux increases concentration distributions. A higher value of thermal radiation heat generation and Eckert number was noticed to improve temperature and velocity distributions. Due to the imposed electromagnetic force, a higher magnetic field is detected to cause an elevation in the velocity distribution. Also, a higher thermal radiation is observed to upsurge the velocity in company with temperature distributions.

This research benefits from biomedical engineering, biological sciences, astrophysics and geophysics. The rheological applications of Williamson fluid finds usefulness in biological sciences. The nanoparticles as considered in this study finds applications in the field of biomedical engineering. Also, the application of the imposed electromagnetic field and magnetic field strength is very useful in the area of astrophysics. A good agreement may be found in the literature on this study’s findings.