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In general, the existing compressor design methods require abundant knowledge and inspiration. The purpose of this study is to identify an intellectual design optimization method that enables a machine to learn how to design it.

The airfoil design process was solved using the reinforcement learning (RL) method. An intellectual method based on a modified deep deterministic policy gradient (DDPG) algorithm was implemented. The new method was applied to agents to learn the design policy under dynamic constraints. The agents explored the design space with the help of a surrogate model and airfoil parameterization.

The agents successfully learned to design the airfoils. The loss coefficients of a controlled diffusion airfoil improved by 1.25% and 3.23% in the two- and four-dimensional design spaces, respectively. The agents successfully learned to design under various constraints. Additionally, the modified DDPG method was compared with a genetic algorithm optimizer, verifying that the former was one to two orders of magnitude faster in policy searching. The NACA65 airfoil was redesigned to verify the generalization.

It is feasible to consider the compressor design as an RL problem. Trained agents can determine and record the design policy and adapt it to different initiations and dynamic constraints. More intelligence is demonstrated than when traditional optimization methods are used. This methodology represents a new, small step toward the intelligent design of compressors.

The purpose of this paper is to study the effect of current-carrying condition on the electrochemical process and atmospheric corrosion behavior of the commercial aluminum alloys.

Potentiodynamic polarization tests were performed to study the electrochemical process of the aluminum alloys. Salt spray tests and weight loss tests were carried out to study the atmospheric corrosion behavior. The corrosion morphology of the alloys was observed, and the products were analyzed.

The corrosion process of four aluminum alloys was accelerated in the current-carrying condition. Moreover, the acceleration effect on A2024 and A7075 was much stronger than that on A1050 and A5052. The main factors would be the differences in microstructure and corrosion resistance between these alloys. As the carried current increased, the corrosion rate and corrosion current density of the aluminum alloys gradually increased, with the protection of the corrosion product film decreasing linearly.

This is a recent study on the corrosion behavior of conductors under current-carrying condition, which truly understands the corrosion status of power grid materials. Relevant results provide support for the corrosion protection and safe service of aluminum alloy in power systems.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.

To understand the seismic behavior of reinforced concrete (RC) beams confined by corroded stirrups, low-reversed cyclic loading tests were carried out on seven RC beam specimens with different stirrup corrosion levels and stirrup ratios to investigate their mechanical characteristics.

The failure mode, hysteresis behavior, skeleton curves, ductility, stiffness degradation and energy dissipation behavior of RC specimens are compared and discussed. The experimental results showed that the restraint of concrete provided by corroded stirrups is reduced, which leads to a decline in seismic performance.

For the specimens with the same ratios of stirrup, as the corrosion level increased, the load-carrying capacity, stiffness, plastic deformation capacity and energy-dissipation capacity dropped significantly. Compared with the uncorroded specimen, the failure modes of specimens with high corrosion level changed from ductile bending failure to brittle failure. For the specimens with the same levels of corrosion, the higher the stirrup ratio was, the stronger the restraint effect of the stirrups on the concrete, and the seismic behavior of the specimens was obviously improved.

In this paper, a total of seven full-size RC beam specimens at joints with different stirrup corrosion levels and stirrup ratios were designed and constructed to explore the influences of corrosion levels and stirrup ratios of stirrups on the seismic performances. The failure modes, strain of reinforcement, hysteretic curves, skeleton curves, stiffness degradation and ductility factor of RC specimens are compared and discussed.

The purpose of this study is determination of cadmium using silver-gold bimetallic nanoparticles (Ag-Au BMNPs) and an aptamer modified glassy carbon electrode.

The maximum response of modified electrode was obtained with, 50 mV pulse amplitude, 20 mV/s scan rate in phosphate buffer of pH 4.0. Ag-Au BMNPs, as the mediators improved electron transmit during the entire electron transfer process and the aptasensor response. Herein, the authors used aptamer as the capture probe to prepare an aptasensor with enhanced stability.

The proposed aptasensor exhibited a wide linearity to cadmium in the range of 0.001–0.100 µg/L with a low detection limit of 0.005×10⁻³ µg/L. The glassy carbon electrodes with Ag-Au BMNPs showed a lower detection limit.

This aptasensor has good reproducibility, stability and repeatability and is cost-effective to regenerate. The specificity and selectivity of the novel modified electrode is tested in the presence of other interfering metal ions such as Fe²⁺, Mn²⁺, Mg²⁺, Sb³⁺ and Bi³⁺. The aptasensor shows 10 times more sensitivity and selectivity for Cd²⁺ ions.

This study aims to examine decision factors for global sourcing, differentiated into transcontinental and continental sourcing to obtain insight into locational aspects of sourcing decisions and global trends. This study analyzed various country perceptions to reveal their influence on sourcing decisions. The country of origin (COO) theory explains why certain country perceptions and images influence purchasing experts in their selection of suppliers.

This study used a two-study approach. In Study 1, the authors conducted discrete choice card experiments with 71 purchasing experts located in Europe and the USA to examine the importance of essential decision factors for global sourcing. Given the clear evidence that location is a factor in sourcing decisions, in Study 2 the authors investigated purchasers’ perceptions and images of countries, adding country ranking experiments on various perceived characteristics such as quality, price and technology.

Study 1 provides evidence that the purchasers’ personal relationship with the supplier plays a decisive role in the supplier selection process. While product quality and location impact sourcing decisions, the attraction of the buying company and cultural barriers are less significant. Interestingly, however, these factors seem as important as price to respondents. This implies that a strong relationship with suppliers and good quality products are essential aspects of a reliable and robust supply chain in the post-COVID-19 era. Examining the locational aspect in detail, Study 2 linked the choice card experiments with country ranking experiments. In this study, the authors found that purchasing experts consider that transcontinental countries such as Japan and China offer significant advantages in terms of price and technology. China has enhanced its quality, which is recognizable in the country ranking experiments. Therefore, decisions on global sourcing are not just based on such high-impact factors as price and availability; country perceptions are also influential. Additionally, the significance of the locational aspect could be linked to certain country images of transcontinental suppliers, as the COO theory describes.

The new approach divides global sourcing into transcontinental and European sourcing to evaluate special decision factors and link these factors to the locational aspect of sourcing decisions. To deepen the clear evidence for the locational aspect and investigate the possible influence of country perceptions, the authors applied the COO theory. This approach enabled authors to show the strong influence of country perception on purchasing departments, which is represented by the locational effect. Hence, the success of transcontinental countries relies not only on factors such as their availability but also on the purchasers’ positive perceptions of these countries in terms of technology and price.

This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.

The purpose of this study is to disclose ontology of DSI as a novel concept in servitization community, explore the research context and themes (i.e. technological and industrial sectors) where DSI emerges, unveil methodological complexities of the research on digital servitization and DSI and provide guidelines for future research avenues regarding DSI.

Bearing in mind the relative novelty of DSI as a concept in servitization literature, the authors adopted a systematic literature review approach to identify 111 peer-reviewed articles published in English language and available in business and management disciplines via scholar databases (Scopus). The analysis of literature discloses descriptive and thematic insights regarding digital servitization and DSI.

The study provides valuable insights from the descriptive and thematic analyses where classification of articles per publication year, citations, methodology/type of the paper, geographical location of data collection, as well as industrial sector and technological contexts are discussed. Moreover, the unique value of this study is observed through its specific focus on the characteristics of DSI-related literature.

The study is among the first of its kind to provide extensive descriptive and thematic insights on the available literature dealing with digital servitization and DSI, mapping out prior research across a wide spectrum of publication outlets and illustrating the chronological evolution of research on digital servitization and DSI.

The study aims to examine the impact of three types of supply chain integration (SCI) on supply chain flexibility (SCF), investigate the impact of SCF on supply chain performance (SCP) and analyse the indirect impact of SCI on SCP by considering the mediating role of SCF within the manufacturing sector of Jordan.

This study used a quantitative approach to validate the study model. An online self-completed questionnaire was used to gather data from 219 participants from managers in various Jordanian manufacturing firms. SmartPLS software was used to perform structural equation modelling to test the formulated hypotheses.

Based on the findings of the study, firms in Jordan's manufacturing sector would benefit from developing an integrative and flexible supply chain to boost SCP in the present volatile, uncertain, complex and speculative market. In addition, SCP was significantly influenced by investments in supply chain management practices related to SCI and SCF. Moreover, SCF significantly moderated the relationship between SCI and SCP. Thus, SCI and SCF assisted firms in reaching their highest potential performance through increased productivity, decreased expenses and increased satisfaction of their customers.

The study employed a cross-sectional design using SCF as a single construct. Future research should look into the specific type of SCFs that have an immense effect on SCP and how these types are affected by the three types of SCI. Furthermore, future research ought to employ probability sampling techniques to improve the generalizability of results or using a longitudinal data-collection design. Finally, additional research should be conducted to validate the findings of this study by replicating it in other specific industries or countries.

The study fills an identified gap based on previous studies by exploring the linkages between SCI, SCF and SCP in the context of manufacturing sector. Moreover, based on the relational view theory, the study proposed an assessment mechanism for SCP for firms based on the link between three types of SCI and SCF.

This study aims to investigate how artificial intelligence (AI)-powered smart home devices affect young consumers' requirements for convenience, support, security and monitoring, as well as their ability to advance environmental sustainability. This study also examines the variables that impact users' motivation to use AI-powered smart home devices, such as perceived value, ease of use, social presence, identity, technology security and the moderating impact of trust.

The responses from residents of Sarawak, Malaysia, were collected through online questionnaires. This study aimed to examine the perceptions of millennials and zillennials towards their trust and adoption of AI-powered devices. This study used a quantitative approach, and the relationships among the study constructs were analysed using partial least squares - structural equation modelling.

The present study found that perceived usefulness, ease of use and social presence were the main motivators among actual and potential users of smart home devices, especially in determining their intentions to use and actual usage. Additionally, there was a moderating effect of trust on the relationship between perceived ease of use, social presence, social identity and intention to use AI-powered devices in smart homes.

To the best of the authors’ knowledge, this is one of the first studies to examine the factors influencing smart technology adoption. This study provided meaningful insights on the development of strategies for the key stakeholders to enhance the adoption and usage of AI-powered smart home devices in Sarawak, one of the promising Borneo states. Additionally, this study contributed to the growing body of knowledge on the associations between technology acceptance model dimensions, intention and actual usage of smart technology, with the moderating impact of trust.