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The COVID-19 pandemic has showcased the lack of resilience found in the global value chains (GVCs) of multinational enterprises (MNEs). Existing evidence shows that MNEs have only recently and slowly started recovering and attempting to rebuild the resilience of their GVCs. This paper analyzes the challenges/inhibitors faced by MNEs in building their resilience through their GVCs.

A four-stage hybrid model was used to identify the interrelationship among the identified inhibitors and to distinguish the most critical ones by ranking them. In the first stage, we employed a modified total interpretive structural modeling (m-TISM) approach to determine the inter-relationship among the inhibitors. Additionally, we identified the inhibitors' driving power and dependency by performing a matrix multiplication applied to classification (MICMAC) analysis. In the second stage, we employed the Pythagorean fuzzy analytic hierarchy process (PF-AHP) method to determine the weight of the criteria. The next stage followed, in which we used the Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method to rank the inhibitors. Finally, we performed a sensitivity analysis to determine the robustness of the framework we had built based on the criteria and inhibitors.

We find business sustainability to have the highest importance and managerial governance as the most critical inhibitor hindering the path to resilience. Based on these insights, we derive four research propositions aimed at strengthening the resilience of such GVCs, followed by their implications for theory and practice.

Our findings contribute to the extant literature by uncovering key inhibitors that act as barriers to MNEs. We link out our findings with a number of propositions that we derive, which may be considered for implementation by MNEs and could help them endow their GVCs with resilience.

This paper aims to investigate the eco-friendly neodymium tartrate (NdTar) inhibitor for mild steel in sodium chloride (NaCl) solution.

The mild steel 1010 coupon was considered for the current study. Weight loss and the electrochemical methods were used to evaluate the inhibitory effects of neodymium chloride (NdCl₃) and NdTar on mild steel in NaCl solution. Scanning electron microscopy, energy-dispersive X-ray analysis and attenuated total reflectance-Fourier transform infrared spectroscopy measurements were carried out to study the morphology and composition of the film, nature of deposits and corrosion products formed in test media on the corroded steel, with the objective of further analyzing the observed behavior of the two inhibitors.

Of the two, NdTar performs better than NdCl₃ because it shields mild steel surfaces for longer. According to the results, when NdCl₃ is present in a corrosive solution, the protective film only comprises Nd/Fe oxide/hydroxide/carbonate. However, when neodymium is coupled with the tartrate group (an organic group) and then added to the NaCl solution, the inhibitor film comprises both bimetallic complexes (Fe-Tar-Nd) and metal oxide/hydroxide/carbonate, which results in a more compact film and has higher inhibition efficiency.

This study evaluated the combined effects of inorganic and organic inhibitors with those of an inorganic inhibitor used alone for mild steel in NaCl solution.

The aim of this study was to investigate the activity of 4-((4-((2-hydroxyethyl)(methyl)amino)benzylidene) amino)-1,5-dimethyl-2-phenyl-1,2-dihydro-3H-pyrazol-3-one (HEMAP), a Schiff base synthesized and characterized for the first time, to the authors’ knowledge, as a novel inhibitor against corrosion of mild steel (MS) in hydrochloric acid solution.

HEMAP was characterized by some spectroscopic methods including High-Resolution Mass Spectrometry (HRMS), Proton Nuclear Magnetic Resonance (1H NMR), Carbon-13 (C13) nuclear magnetic resonance (13C NMR) and Fourier Transform Infrared Spectroscopy (FT-IR). Then, the inhibition efficiency of HEMAP on MS in a hydrochloric acid solution was investigated by potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). To explain the inhibition mechanism, the surface charge, adsorption isotherms and thermodynamic parameters of MS in the inhibitor solution were studied.

EIS tests displayed that the highest inhibition efficiency was calculated approximately as 99.5% for 5 × 10⁻² M HEMAP in 1 M HCl solution. The adsorption of HEMAP on the MS surface was found to be compatible with the Langmuir model isotherm. The thermodynamic parameter results showed that the standard free energy of adsorption of HEMAP on the MS surface was found to be more chemical than physical.

This study is important in terms of demonstrating the performance of the first synthesized HEMAP molecule as an inhibitor against the corrosion of MS in acidic media. EIS tests displayed that the highest inhibition efficiency was calculated approximately as 99.5% for 5 × 10⁻² M HEMAP in 1 M HCl solution.

This study aims to prevent mild steel (MS) against corrosion in 0.5 M HCl solution, 2-amino-4-methoxy-6-methyl-1,3,5-triazine was used. The effectiveness of the compound as a corrosion inhibitor was studied via electrochemical, surface and theoretical calculation techniques.

For concentrations ranging from 0.5 to 10.0 mM, almost similar polarization resistances were obtained from electrochemical impedance spectroscopy (EIS) and linear polarization resistance tests. It also investigated inhibitive activity of 2-amino-4-methoxy-6-methyl-1,3,5-triazine on the steel surface using scanning electron and atomic force microscope instruments. Langmuir adsorption is the best matched isotherm for the adsorption of the inhibitor to the steel surface.

EIS method was used to determine inhibition efficiency, which was determined to be 95.7% for 10.0 mM inhibitor containing acid solution. Density functional theory’s predictions for quantum chemistry agreed well with the other experimental results.

The methods used in this study are effective and applicable; the used organic inhibitor is 2-amino-4-methoxy-6-methyl-1,3,5-triazine; and protective effectiveness is important, which is crucial for the task of MS corrosion prevention.

This paper aims to study the corrosion inhibition behavior of imidazopyridine and its three derivatives on brass.

The authors performed weight loss experiments, electrochemical experiments including the polarization curve and electrochemical impedance spectrum, corrosion morphology observation using scanning electron microscope (SEM) and atomic force microscope (AFM) and surface composition analysis via X-ray photoelectron spectroscopy (XPS) to analyze the corrosion inhibition behavior of imidazopyridine and its three derivatives on brass by using quantum chemical calculation (Gaussian 09), molecular dynamics simulation (M-S) and Langmuir adsorption isotherm.

According to the results, imidazole-pyridine and its derivatives were found to be modest or moderately mixed corrosion inhibitors; moreover, they were spontaneously adsorbed on the metal surface in a single-layer, mixed adsorption mode.

The corrosion inhibition properties of pyrazolo-[1,2-a]pyridine and its derivatives on brass in sulfuric acid solution were analyzed through weight loss and electrochemical experiments. Moreover, SEM and AFM were simultaneously used to observe the corrosion appearance. Furthermore, XPS was used to analyze the surface. Then, Gaussian 09 and M-S were combined along with the Langmuir adsorption isotherm to investigate the corrosion inhibition mechanism of imidazole-[1,2-a]pyridine and its derivatives.

This study aims to investigate the corrosion inhibitor effect of migrating corrosion inhibitor (MCI) on Q235 steel in high alkaline environment under cathodic polarization.

This study investigated the electrochemical characteristics of Q235 steel with and without MCI by polarization curve and electrochemical impedance spectroscopy. Besides, the surface composition of Q235 steel under different environments was analyzed by X-ray photoelectron spectroscopy. In addition, the migration characteristic of MCI and the adsorption behavior of MCI under cathodic polarization were studied using Raman spectroscopy.

Diethanolamine (DEA) and N, N-dimethylethanolamine (DMEA) can inhibit the increase of Fe(II) in the oxide film of Q235 steel under cathodic polarization. The adsorption stability of DMEA film was higher under cathodic polarization potential, showing a higher corrosion inhibition ability. The corrosion inhibition mechanism of DEA and DMEA under cathodic polarization potential was proposed.

The MCI has a broad application prospect in the repair of damaged reinforced concrete due to its unique migratory characteristics. The interaction between MCIs, rebar and concrete with different compositions has been studied, but the passivation behavior of the steel interface in the presence of both the migrating electric field and corrosion inhibitors has been neglected. And it was investigated in this paper.

This study aims to explore the synergistic effect of oxide nanoparticles (ZnO, Fe₂O₃, SiO₂) and cerium nitrate inhibitor on anti-corrosion performance of epoxy coating. First, cerium nitrate inhibitors are absorbed on the surface of various oxide nanoparticles. Thereafter, epoxy nanocomposite coatings have been fabricated on carbon steel substrate using these oxide@Ce nanoparticles as both nano-fillers and nano-inhibitors.

To evaluate the impact of oxides@Ce nanoparticles on mechanical properties of epoxy coating, the abrasion resistance and impact resistance of epoxy coatings have been examined. To study the impact of oxides@Ce nanoparticles on anti-corrosion performance of epoxy coating for steel, the electrochemical impedance spectroscopy has been carried out in 3% NaCl solution.

ZnO@Ce3+ and SiO2@Ce3+ nanoparticles provide more enhancement in the epoxy pore network than modification of the epoxy/steel interface. Whereas, Fe2O3@Ce3+ nanoparticles have more to do with modification of the epoxy/steel interface than to change the epoxy pore network.

Incorporation of both oxide nanoparticles and inorganic inhibitor into the epoxy resin is a promising approach for enhancing the anti-corrosion performance of carbon steel.

Wearable health devices (WHDs) have demonstrated significant potential in assisting elderly adults with proactive health management by utilizing sensors to record and monitor various aspects of their health, including physical activity, heart rate, etc. However, limited research has systematically explored older adults’ continued usage intention toward WHD. By utilizing the extended unified theory of acceptance and use of technology (UTAUT2), this paper aims to probe the precursors of elderly adults’ continuance intention to use WHD from an enabler–inhibitor perspective.

The research model was developed based on UTAUT2 and examined utilizing the partial least squares technique (PLS). The research data were collected through in-person meetings with older people (n = 272) in four cities in China.

Results reveal that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic values and perceived complexity are the positive predictors of elderly adults’ continuance intention to use WHDs. Technology-related anxiety and usage cost negatively influence the formation of older people’s continuance intention.

This work is an original empirical investigation that draws on several theories as guiding frameworks. It adds to the existing literature on the usage of wearable technologies and offers insights into how the elderly’s intentions to continue using WHDs can be developed. This study broadens the scope of the UTAUT2 application and presents an alternative theoretical framework that can be utilized in future research on the usage behavior of wearable devices by individuals.

Decision-making, reinforced by artificial intelligence (AI), is predicted to become potent tool within the domain of supply chain management. Considering the importance of this subject, the purpose of this study is to explore the triggers and technological inhibitors affecting the adoption of AI. This study also aims to identify three-dimensional triggers, notably those linked to environmental, social, and governance (ESG), as well as technological inhibitors.

Drawing upon a six-step systematic review following the preferred reporting items for systematic reviews and meta analysis (PRISMA) guidelines, a broad range of journal publications was recognized, with a thematic analysis under the lens of the ESG framework, offering a unique perspective on factors triggering and inhibiting AI adoption in the supply chain.

In the environmental dimension, triggers include product waste reduction and greenhouse gas emissions reduction, highlighting the potential of AI in promoting sustainability and environmental responsibility. In the social dimension, triggers encompass product security and quality, as well as social well-being, indicating how AI can contribute to ensuring safe and high-quality products and enhancing societal welfare. In the governance dimension, triggers involve agile and lean practices, cost reduction, sustainable supplier selection, circular economy initiatives, supply chain risk management, knowledge sharing and the synergy between supply and demand. The inhibitors in the technological category present challenges, encompassing the lack of regulations and rules, data security and privacy concerns, responsible and ethical AI considerations, performance and ethical assessment difficulties, poor data quality, group bias and the need to achieve synergy between AI and human decision-makers.

Despite the use of PRISMA guidelines to ensure a comprehensive search and screening process, it is possible that some relevant studies in other databases and industry reports may have been missed. In light of this, the selected studies may not have fully captured the diversity of triggers and technological inhibitors. The extraction of themes from the selected papers is subjective in nature and relies on the interpretation of researchers, which may introduce bias.

The research contributes to the field by conducting a comprehensive analysis of the diverse factors that trigger or inhibit AI adoption, providing valuable insights into their impact. By incorporating the ESG protocol, the study offers a holistic evaluation of the dimensions associated with AI adoption in the supply chain, presenting valuable implications for both industry professionals and researchers. The originality lies in its in-depth examination of the multifaceted aspects of AI adoption, making it a valuable resource for advancing knowledge in this area.

The purpose of the study is to investigate the impact of perceived value and academic entitlement on the online engagement of university students. The mediating effect of technostress inhibitor and teacher behavior between perceived value, entitlement and student engagement was also examined.

The study used a quantitative research methodology, with data collected through a survey of 304 undergraduate students from a public university in Bahrain.

The findings showed that perceived value and academic entitlement were significant predictors of online student engagement. At the same time, only technostress inhibitor was found to mediate those associations. An unexpected result was entitlement's positive and significant impact on student engagement.

University decision-makers are strongly advised to enhance perceived value and support mechanisms for engagement, address technology-related concerns and improve teacher capacity and students' online learning experience.

The study makes a distinct contribution by investigating how perceived value, academic entitlement, technostress inhibitors and teacher behavior influence student engagement in the online higher education context.